{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@题目5 生成对抗网络实战——用GAN生成人物头像"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 建立GAN模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.utils import data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生成器，将噪声信号通过转置卷积生成 3x64x64特征图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Generator(torch.nn.Module):\n",
    "    def __init__(self,in_size,out_size,out_channel):\n",
    "        super(Generator,self).__init__()\n",
    "        self.out_size=out_size\n",
    "        self.in_size=in_size\n",
    "        self.out_channel=out_channel\n",
    "        self.main=torch.nn.Sequential(\n",
    "            #Block 1 将输入噪声序列通过转置卷积变换为 out_size*8*4*4特征图\n",
    "            torch.nn.ConvTranspose2d(in_size,out_size*8,4,1,0,bias=False),\n",
    "            torch.nn.BatchNorm2d(out_size*8),\n",
    "            torch.nn.ReLU(True),\n",
    "            #Block 2 通过转置卷积变换为 out_size*4*8*8特征图\n",
    "            torch.nn.ConvTranspose2d(out_size*8,out_size*4,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(out_size*4),\n",
    "            torch.nn.ReLU(True),\n",
    "            #Block 3 通过转置卷积变换为 out_size*2*16*16特征图\n",
    "            torch.nn.ConvTranspose2d(out_size*4,out_size*2,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(out_size*2),\n",
    "            torch.nn.ReLU(True),\n",
    "            #Block 3 通过转置卷积变换为 out_size*32*32特征图\n",
    "            torch.nn.ConvTranspose2d(out_size*2,out_size,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(out_size),\n",
    "            torch.nn.ReLU(True),\n",
    "            #Block 4 通过转置卷积变换为 out_channel*64*64特征图\n",
    "            torch.nn.ConvTranspose2d(out_size,out_channel,4,2,1,bias=False),\n",
    "            torch.nn.Tanh()\n",
    "        )\n",
    "    def forward(self,x):\n",
    "        return self.main(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 判别器，CNN网络，通过5次卷积判别输出真假"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Discriminator(torch.nn.Module):\n",
    "    def __init__(self,in_size=64,in_channel=3):\n",
    "        super(Discriminator,self).__init__()\n",
    "        self.in_size=in_size\n",
    "        self.in_channel=in_channel\n",
    "        self.main=torch.nn.Sequential(\n",
    "            #Block1 将输入图片(3*64*64卷积为64*32*32)\n",
    "            torch.nn.Conv2d(in_channel,in_size,4,2,1,bias=False),\n",
    "            torch.nn.LeakyReLU(0.2,inplace=True),\n",
    "            #Block2 通过卷积得到64*2*16*16\n",
    "            torch.nn.Conv2d(in_size,in_size*2,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(in_size*2),\n",
    "            torch.nn.LeakyReLU(0.2,inplace=True),\n",
    "            #Block3 通过卷积得到64*2*2*8*8\n",
    "            torch.nn.Conv2d(in_size*2,in_size*4,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(in_size*4),\n",
    "            torch.nn.LeakyReLU(0.2,inplace=True),\n",
    "            #Block4 通过卷积得到64*2*2*2*4*4\n",
    "            torch.nn.Conv2d(in_size*4,in_size*8,4,2,1,bias=False),\n",
    "            torch.nn.BatchNorm2d(in_size*8),\n",
    "            torch.nn.LeakyReLU(0.2,inplace=True),\n",
    "            #Block5 通过卷积得到1*1*1\n",
    "            torch.nn.Conv2d(in_size*8,1,4,1,0,bias=False),\n",
    "            torch.nn.Sigmoid()\n",
    "        )\n",
    "    def forward(self,x):\n",
    "        return self.main(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据加载和其他配置"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 配置图片大小64x64，batch_size设置为64，RGB通道，输入噪声序列长度为100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size=64\n",
    "image_size=64\n",
    "out_channel=3\n",
    "out_size=64\n",
    "in_size=100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 采用BCE损失函数，设置真实图片标签为1，实例化生成器和判别器，设置Adam优化器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss=torch.nn.BCELoss()\n",
    "real_label=1.0\n",
    "fake_label=0.0\n",
    "dev=torch.device('cuda:0')\n",
    "net_G=Generator(in_size,out_size,out_channel).to(dev)\n",
    "net_D=Discriminator(out_size,out_channel).to(dev)\n",
    "lr=0.0003\n",
    "beta1=0.5\n",
    "optimizer_G=torch.optim.Adam(net_G.parameters(),lr,betas=(beta1,0.999))\n",
    "optimizer_D=torch.optim.Adam(net_D.parameters(),lr,betas=(beta1,0.999))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读入头像图片，并进行归一化，构建迭代器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchvision.datasets as datasets\n",
    "import torchvision.transforms as transforms\n",
    "train_data=datasets.ImageFolder(\n",
    "    root='./data/face/',\n",
    "    transform=transforms.Compose([transforms.Resize(image_size),transforms.CenterCrop(image_size),transforms.ToTensor(),transforms.Normalize((0.5,0.5,0.5),(0.5,0.5,0.5))])\n",
    ")\n",
    "data_load=data.DataLoader(train_data,batch_size=batch_size,shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "epochs=100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchvision.utils as vutils\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 随机生成一个batch_size的噪声序列，从而验证训练过程中生成效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fixed_noise=torch.randn(64,in_size,1,1,device=dev)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "iters=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_list=[]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练模型 更新权重参数并显示loss值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 0 ,i: 0 ,Loss_D: 1.4849486351013184 ,Loss_G: 3.1297473907470703 ,D(x): 0.42732858657836914 ,D(G(z)) 9.99927565138886\n",
      "epoch: 0 ,i: 50 ,Loss_D: 1.328763723373413 ,Loss_G: 8.346368789672852 ,D(x): 0.8657563924789429 ,D(G(z)) 1372.0402833826058\n",
      "epoch: 0 ,i: 100 ,Loss_D: 0.5012184381484985 ,Loss_G: 4.024028778076172 ,D(x): 0.6654468178749084 ,D(G(z)) 2.347338932174659\n",
      "epoch: 0 ,i: 150 ,Loss_D: 0.7258259057998657 ,Loss_G: 2.7216899394989014 ,D(x): 0.6996279954910278 ,D(G(z)) 3.6698800950310817\n",
      "epoch: 0 ,i: 200 ,Loss_D: 0.9182283282279968 ,Loss_G: 4.508383750915527 ,D(x): 0.8607712388038635 ,D(G(z)) 38.44593544333693\n",
      "epoch: 0 ,i: 250 ,Loss_D: 0.4399852752685547 ,Loss_G: 4.585675239562988 ,D(x): 0.8269513845443726 ,D(G(z)) 14.614492106704763\n",
      "epoch: 0 ,i: 300 ,Loss_D: 0.8411442041397095 ,Loss_G: 7.83412504196167 ,D(x): 0.9413596391677856 ,D(G(z)) 1012.2475455604581\n",
      "epoch: 0 ,i: 350 ,Loss_D: 1.051711916923523 ,Loss_G: 6.63861083984375 ,D(x): 0.4848030209541321 ,D(G(z)) 0.7924052196065531\n",
      "epoch: 0 ,i: 400 ,Loss_D: 0.32188087701797485 ,Loss_G: 3.1596319675445557 ,D(x): 0.8928238749504089 ,D(G(z)) 3.398619600621586\n",
      "epoch: 0 ,i: 450 ,Loss_D: 4.201562881469727 ,Loss_G: 9.477324485778809 ,D(x): 0.04729355126619339 ,D(G(z)) 0.1957723566877242\n",
      "epoch: 0 ,i: 500 ,Loss_D: 0.8661561012268066 ,Loss_G: 3.8310599327087402 ,D(x): 0.6991928815841675 ,D(G(z)) 12.456808968894672\n",
      "epoch: 0 ,i: 550 ,Loss_D: 0.944994330406189 ,Loss_G: 6.358610153198242 ,D(x): 0.946872353553772 ,D(G(z)) 241.885699066897\n",
      "epoch: 0 ,i: 600 ,Loss_D: 0.6702014207839966 ,Loss_G: 3.380756378173828 ,D(x): 0.6568900942802429 ,D(G(z)) 2.8159255770421927\n",
      "epoch: 0 ,i: 650 ,Loss_D: 1.0170890092849731 ,Loss_G: 2.89025616645813 ,D(x): 0.5847182273864746 ,D(G(z)) 4.248659365473731\n",
      "epoch: 0 ,i: 700 ,Loss_D: 1.4788151979446411 ,Loss_G: 6.957306385040283 ,D(x): 0.3614315986633301 ,D(G(z)) 0.8481590168227022\n",
      "epoch: 0 ,i: 750 ,Loss_D: 1.1600629091262817 ,Loss_G: 7.826180458068848 ,D(x): 0.970146894454956 ,D(G(z)) 1010.0334539615175\n",
      "epoch: 1 ,i: 0 ,Loss_D: 0.2726592421531677 ,Loss_G: 2.353184700012207 ,D(x): 0.9112343788146973 ,D(G(z)) 1.1254765796145987\n",
      "epoch: 1 ,i: 50 ,Loss_D: 0.7046545147895813 ,Loss_G: 4.380298614501953 ,D(x): 0.7324719429016113 ,D(G(z)) 13.76666498738968\n",
      "epoch: 1 ,i: 100 ,Loss_D: 1.1542664766311646 ,Loss_G: 7.291134834289551 ,D(x): 0.8447418212890625 ,D(G(z)) 550.2952784532414\n",
      "epoch: 1 ,i: 150 ,Loss_D: 0.7909595966339111 ,Loss_G: 8.15121078491211 ,D(x): 0.9815143346786499 ,D(G(z)) 873.981247221868\n",
      "epoch: 1 ,i: 200 ,Loss_D: 0.5765030980110168 ,Loss_G: 4.801685333251953 ,D(x): 0.8533087968826294 ,D(G(z)) 24.95095073680444\n",
      "epoch: 1 ,i: 250 ,Loss_D: 0.2124413549900055 ,Loss_G: 2.5319252014160156 ,D(x): 0.8510912656784058 ,D(G(z)) 0.28074654598109405\n",
      "epoch: 1 ,i: 300 ,Loss_D: 0.3126487731933594 ,Loss_G: 4.9810028076171875 ,D(x): 0.8002437949180603 ,D(G(z)) 4.665684361019862\n",
      "epoch: 1 ,i: 350 ,Loss_D: 0.5105801224708557 ,Loss_G: 4.0437774658203125 ,D(x): 0.6714891195297241 ,D(G(z)) 0.8971164971926937\n",
      "epoch: 1 ,i: 400 ,Loss_D: 0.48860597610473633 ,Loss_G: 2.7619829177856445 ,D(x): 0.7618186473846436 ,D(G(z)) 1.419816712141152\n",
      "epoch: 1 ,i: 450 ,Loss_D: 0.7210689783096313 ,Loss_G: 4.0501203536987305 ,D(x): 0.6833928823471069 ,D(G(z)) 9.248518181565366\n",
      "epoch: 1 ,i: 500 ,Loss_D: 1.3136621713638306 ,Loss_G: 4.822905540466309 ,D(x): 0.371567964553833 ,D(G(z)) 0.20457845657396823\n",
      "epoch: 1 ,i: 550 ,Loss_D: 0.38843387365341187 ,Loss_G: 5.856616973876953 ,D(x): 0.8700681328773499 ,D(G(z)) 40.13251053113738\n",
      "epoch: 1 ,i: 600 ,Loss_D: 0.7667228579521179 ,Loss_G: 4.19248104095459 ,D(x): 0.5521091818809509 ,D(G(z)) 0.7178404117532196\n",
      "epoch: 1 ,i: 650 ,Loss_D: 0.5001101493835449 ,Loss_G: 4.4060516357421875 ,D(x): 0.767778754234314 ,D(G(z)) 7.642381075801651\n",
      "epoch: 1 ,i: 700 ,Loss_D: 0.23678115010261536 ,Loss_G: 5.68732213973999 ,D(x): 0.8846872448921204 ,D(G(z)) 15.239771230957663\n",
      "epoch: 1 ,i: 750 ,Loss_D: 0.5323525071144104 ,Loss_G: 6.506677150726318 ,D(x): 0.9200682640075684 ,D(G(z)) 115.275821970032\n",
      "epoch: 2 ,i: 0 ,Loss_D: 0.2474593222141266 ,Loss_G: 6.27105712890625 ,D(x): 0.9026197195053101 ,D(G(z)) 19.390419361591068\n",
      "epoch: 2 ,i: 50 ,Loss_D: 0.20145109295845032 ,Loss_G: 2.1211812496185303 ,D(x): 0.9500929713249207 ,D(G(z)) 0.872871948872988\n",
      "epoch: 2 ,i: 100 ,Loss_D: 0.8991279602050781 ,Loss_G: 5.012134075164795 ,D(x): 0.5328288078308105 ,D(G(z)) 0.3983509234975449\n",
      "epoch: 2 ,i: 150 ,Loss_D: 0.3533029556274414 ,Loss_G: 5.037044525146484 ,D(x): 0.9588803052902222 ,D(G(z)) 21.59821472256457\n",
      "epoch: 2 ,i: 200 ,Loss_D: 0.48031413555145264 ,Loss_G: 3.794799327850342 ,D(x): 0.7279456853866577 ,D(G(z)) 1.7608236716857513\n",
      "epoch: 2 ,i: 250 ,Loss_D: 0.9087885022163391 ,Loss_G: 3.0778632164001465 ,D(x): 0.5344550609588623 ,D(G(z)) 0.11562535336299488\n",
      "epoch: 2 ,i: 300 ,Loss_D: 0.49127984046936035 ,Loss_G: 3.498582363128662 ,D(x): 0.774320662021637 ,D(G(z)) 4.400568284709308\n",
      "epoch: 2 ,i: 350 ,Loss_D: 0.3076465129852295 ,Loss_G: 4.633386611938477 ,D(x): 0.831433892250061 ,D(G(z)) 4.653753602137765\n",
      "epoch: 2 ,i: 400 ,Loss_D: 0.13049814105033875 ,Loss_G: 3.538252830505371 ,D(x): 0.9653637409210205 ,D(G(z)) 1.6587950269682363\n",
      "epoch: 2 ,i: 450 ,Loss_D: 1.4044976234436035 ,Loss_G: 12.102636337280273 ,D(x): 0.9823251962661743 ,D(G(z)) 46701.85087886078\n",
      "epoch: 2 ,i: 500 ,Loss_D: 0.8374271392822266 ,Loss_G: 5.400123119354248 ,D(x): 0.5386645197868347 ,D(G(z)) 0.3630681074913785\n",
      "epoch: 2 ,i: 550 ,Loss_D: 0.25169992446899414 ,Loss_G: 4.606418609619141 ,D(x): 0.8301087617874146 ,D(G(z)) 2.171380468681481\n",
      "epoch: 2 ,i: 600 ,Loss_D: 0.19955646991729736 ,Loss_G: 5.177054405212402 ,D(x): 0.8791599273681641 ,D(G(z)) 5.7635424591852695\n",
      "epoch: 2 ,i: 650 ,Loss_D: 1.1964035034179688 ,Loss_G: 11.15394401550293 ,D(x): 0.9745907783508301 ,D(G(z)) 15243.11689827046\n",
      "epoch: 2 ,i: 700 ,Loss_D: 0.9189678430557251 ,Loss_G: 8.435853958129883 ,D(x): 0.9162331223487854 ,D(G(z)) 1243.6867708845389\n",
      "epoch: 2 ,i: 750 ,Loss_D: 0.48849159479141235 ,Loss_G: 3.169137954711914 ,D(x): 0.7073884010314941 ,D(G(z)) 0.7477418808282335\n",
      "epoch: 3 ,i: 0 ,Loss_D: 0.3000548481941223 ,Loss_G: 5.619437217712402 ,D(x): 0.8913248777389526 ,D(G(z)) 27.819032133792604\n",
      "epoch: 3 ,i: 50 ,Loss_D: 0.2296246737241745 ,Loss_G: 4.693091869354248 ,D(x): 0.9092699289321899 ,D(G(z)) 9.993859825031352\n",
      "epoch: 3 ,i: 100 ,Loss_D: 0.4259946644306183 ,Loss_G: 5.092891693115234 ,D(x): 0.7426660656929016 ,D(G(z)) 2.651137918463617\n",
      "epoch: 3 ,i: 150 ,Loss_D: 0.14905662834644318 ,Loss_G: 3.3095178604125977 ,D(x): 0.9815269112586975 ,D(G(z)) 2.3735747548134727\n",
      "epoch: 3 ,i: 200 ,Loss_D: 0.2801641821861267 ,Loss_G: 5.506084442138672 ,D(x): 0.9172632098197937 ,D(G(z)) 25.28251208086974\n",
      "epoch: 3 ,i: 250 ,Loss_D: 0.29035434126853943 ,Loss_G: 2.8303921222686768 ,D(x): 0.940024197101593 ,D(G(z)) 2.2282537254009886\n",
      "epoch: 3 ,i: 300 ,Loss_D: 0.2877991795539856 ,Loss_G: 4.500265121459961 ,D(x): 0.8406625986099243 ,D(G(z)) 3.6073531102275327\n",
      "epoch: 3 ,i: 350 ,Loss_D: 0.18246260285377502 ,Loss_G: 3.7984671592712402 ,D(x): 0.9941290020942688 ,D(G(z)) 3.2231285998951233\n",
      "epoch: 3 ,i: 400 ,Loss_D: 0.2310275137424469 ,Loss_G: 5.9631805419921875 ,D(x): 0.9122279286384583 ,D(G(z)) 23.95075456873811\n",
      "epoch: 3 ,i: 450 ,Loss_D: 0.3416525721549988 ,Loss_G: 4.5374345779418945 ,D(x): 0.8523464798927307 ,D(G(z)) 6.453651144801733\n",
      "epoch: 3 ,i: 500 ,Loss_D: 0.33632194995880127 ,Loss_G: 4.764426231384277 ,D(x): 0.804215669631958 ,D(G(z)) 4.173959556967747\n",
      "epoch: 3 ,i: 550 ,Loss_D: 0.6057627201080322 ,Loss_G: 4.345183372497559 ,D(x): 0.6244750022888184 ,D(G(z)) 0.76373544511446\n",
      "epoch: 3 ,i: 600 ,Loss_D: 0.3239441514015198 ,Loss_G: 4.349050045013428 ,D(x): 0.875441312789917 ,D(G(z)) 8.468571261367615\n",
      "epoch: 3 ,i: 650 ,Loss_D: 0.22365808486938477 ,Loss_G: 4.226842880249023 ,D(x): 0.9058818817138672 ,D(G(z)) 4.343088137770962\n",
      "epoch: 3 ,i: 700 ,Loss_D: 0.2759241759777069 ,Loss_G: 9.433185577392578 ,D(x): 0.8051701188087463 ,D(G(z)) 3.9038552856459003\n",
      "epoch: 3 ,i: 750 ,Loss_D: 0.8133484721183777 ,Loss_G: 11.643651962280273 ,D(x): 0.9461318254470825 ,D(G(z)) 21101.613756400187\n",
      "epoch: 4 ,i: 0 ,Loss_D: 0.4601070284843445 ,Loss_G: 6.593871116638184 ,D(x): 0.8503215312957764 ,D(G(z)) 73.83534542749074\n",
      "epoch: 4 ,i: 50 ,Loss_D: 0.15098755061626434 ,Loss_G: 7.184925079345703 ,D(x): 0.8847500681877136 ,D(G(z)) 5.222182433840667\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 4 ,i: 100 ,Loss_D: 0.6749919056892395 ,Loss_G: 7.825328826904297 ,D(x): 0.9990307092666626 ,D(G(z)) 560.3297015537111\n",
      "epoch: 4 ,i: 150 ,Loss_D: 0.3155541718006134 ,Loss_G: 4.295351028442383 ,D(x): 0.8847374320030212 ,D(G(z)) 6.924708605633062\n",
      "epoch: 4 ,i: 200 ,Loss_D: 0.11825922876596451 ,Loss_G: 4.34144401550293 ,D(x): 0.9739115238189697 ,D(G(z)) 3.7884173728211414\n",
      "epoch: 4 ,i: 250 ,Loss_D: 0.5322386026382446 ,Loss_G: 5.846255779266357 ,D(x): 0.922351062297821 ,D(G(z)) 63.63509808860323\n",
      "epoch: 4 ,i: 300 ,Loss_D: 0.1620003879070282 ,Loss_G: 6.203725814819336 ,D(x): 0.8906782865524292 ,D(G(z)) 6.259646002877654\n",
      "epoch: 4 ,i: 350 ,Loss_D: 0.7897205352783203 ,Loss_G: 6.258270263671875 ,D(x): 0.5489136576652527 ,D(G(z)) 0.18408589170140868\n",
      "epoch: 4 ,i: 400 ,Loss_D: 0.1061018705368042 ,Loss_G: 3.800718307495117 ,D(x): 0.9383535385131836 ,D(G(z)) 0.8836446737687713\n",
      "epoch: 4 ,i: 450 ,Loss_D: 0.36240053176879883 ,Loss_G: 4.238956451416016 ,D(x): 0.9911907315254211 ,D(G(z)) 11.332378092767657\n",
      "epoch: 4 ,i: 500 ,Loss_D: 0.33065634965896606 ,Loss_G: 6.998863220214844 ,D(x): 0.960320234298706 ,D(G(z)) 150.18368206684457\n",
      "epoch: 4 ,i: 550 ,Loss_D: 0.4425831735134125 ,Loss_G: 2.673797130584717 ,D(x): 0.7694990634918213 ,D(G(z)) 1.2520123871826516\n",
      "epoch: 4 ,i: 600 ,Loss_D: 0.13112659752368927 ,Loss_G: 6.124698638916016 ,D(x): 0.893785834312439 ,D(G(z)) 1.5829859405984714\n",
      "epoch: 4 ,i: 650 ,Loss_D: 0.25532716512680054 ,Loss_G: 5.201925277709961 ,D(x): 0.8903578519821167 ,D(G(z)) 14.283066869570824\n",
      "epoch: 4 ,i: 700 ,Loss_D: 0.3873503506183624 ,Loss_G: 6.266808986663818 ,D(x): 0.9007521271705627 ,D(G(z)) 78.5480479515864\n",
      "epoch: 4 ,i: 750 ,Loss_D: 0.5036618113517761 ,Loss_G: 2.186535358428955 ,D(x): 0.700192928314209 ,D(G(z)) 0.5802625561365643\n",
      "epoch: 5 ,i: 0 ,Loss_D: 0.17299915850162506 ,Loss_G: 5.884726524353027 ,D(x): 0.8686065673828125 ,D(G(z)) 1.5328738668577953\n",
      "epoch: 5 ,i: 50 ,Loss_D: 0.2566036283969879 ,Loss_G: 5.09092903137207 ,D(x): 0.8078556060791016 ,D(G(z)) 1.6708461102325238\n",
      "epoch: 5 ,i: 100 ,Loss_D: 0.21594193577766418 ,Loss_G: 5.572232723236084 ,D(x): 0.9380238056182861 ,D(G(z)) 23.038858119120405\n",
      "epoch: 5 ,i: 150 ,Loss_D: 0.18707123398780823 ,Loss_G: 3.443535566329956 ,D(x): 0.993741512298584 ,D(G(z)) 3.0346630607883314\n",
      "epoch: 5 ,i: 200 ,Loss_D: 0.5541549921035767 ,Loss_G: 7.269786834716797 ,D(x): 0.9127582907676697 ,D(G(z)) 234.00244278179255\n",
      "epoch: 5 ,i: 250 ,Loss_D: 0.3333691358566284 ,Loss_G: 6.072004318237305 ,D(x): 0.9295541048049927 ,D(G(z)) 46.5421391780031\n",
      "epoch: 5 ,i: 300 ,Loss_D: 0.10087811201810837 ,Loss_G: 6.29304313659668 ,D(x): 0.9245041608810425 ,D(G(z)) 3.989175988605921\n",
      "epoch: 5 ,i: 350 ,Loss_D: 0.29076942801475525 ,Loss_G: 3.548591136932373 ,D(x): 0.8585115671157837 ,D(G(z)) 2.1288572355398108\n",
      "epoch: 5 ,i: 400 ,Loss_D: 0.11477822065353394 ,Loss_G: 4.824137210845947 ,D(x): 0.9367470741271973 ,D(G(z)) 3.6555895188039433\n",
      "epoch: 5 ,i: 450 ,Loss_D: 0.2931813895702362 ,Loss_G: 5.152745246887207 ,D(x): 0.810245156288147 ,D(G(z)) 2.751343558049512\n",
      "epoch: 5 ,i: 500 ,Loss_D: 0.09653156250715256 ,Loss_G: 4.885770797729492 ,D(x): 0.9746693968772888 ,D(G(z)) 5.927121175509758\n",
      "epoch: 5 ,i: 550 ,Loss_D: 0.3262515664100647 ,Loss_G: 3.9055631160736084 ,D(x): 0.8110246062278748 ,D(G(z)) 2.0472183992935307\n",
      "epoch: 5 ,i: 600 ,Loss_D: 0.1676752269268036 ,Loss_G: 3.872772693634033 ,D(x): 0.8760950565338135 ,D(G(z)) 0.8399639309242986\n",
      "epoch: 5 ,i: 650 ,Loss_D: 0.3165260851383209 ,Loss_G: 6.007297515869141 ,D(x): 0.9514088034629822 ,D(G(z)) 48.0759526545411\n",
      "epoch: 5 ,i: 700 ,Loss_D: 0.058441273868083954 ,Loss_G: 4.7029290199279785 ,D(x): 0.954386293888092 ,D(G(z)) 0.4896889711635436\n",
      "epoch: 5 ,i: 750 ,Loss_D: 0.11791136860847473 ,Loss_G: 4.405793190002441 ,D(x): 0.9461649656295776 ,D(G(z)) 2.8197945953678176\n",
      "epoch: 6 ,i: 0 ,Loss_D: 0.44809484481811523 ,Loss_G: 4.324701309204102 ,D(x): 0.8845868110656738 ,D(G(z)) 8.718567334270578\n",
      "epoch: 6 ,i: 50 ,Loss_D: 0.18490998446941376 ,Loss_G: 1.7558813095092773 ,D(x): 0.9611766338348389 ,D(G(z)) 0.5342604454562891\n",
      "epoch: 6 ,i: 100 ,Loss_D: 0.21089857816696167 ,Loss_G: 4.88913106918335 ,D(x): 0.887114942073822 ,D(G(z)) 4.233343470998895\n",
      "epoch: 6 ,i: 150 ,Loss_D: 0.16638164222240448 ,Loss_G: 6.01252555847168 ,D(x): 0.9799839854240417 ,D(G(z)) 25.22311190620925\n",
      "epoch: 6 ,i: 200 ,Loss_D: 0.2693940997123718 ,Loss_G: 2.917764663696289 ,D(x): 0.872644305229187 ,D(G(z)) 1.2339842917058172\n",
      "epoch: 6 ,i: 250 ,Loss_D: 0.21102406084537506 ,Loss_G: 3.344398021697998 ,D(x): 0.8551356792449951 ,D(G(z)) 0.3593529496115305\n",
      "epoch: 6 ,i: 300 ,Loss_D: 0.30538469552993774 ,Loss_G: 3.540987491607666 ,D(x): 0.8512277007102966 ,D(G(z)) 2.3604285275737054\n",
      "epoch: 6 ,i: 350 ,Loss_D: 0.09546814858913422 ,Loss_G: 4.748052597045898 ,D(x): 0.9872913956642151 ,D(G(z)) 4.821584049476179\n",
      "epoch: 6 ,i: 400 ,Loss_D: 0.15985935926437378 ,Loss_G: 5.759381294250488 ,D(x): 0.8911037445068359 ,D(G(z)) 4.131833472861345\n",
      "epoch: 6 ,i: 450 ,Loss_D: 0.24468322098255157 ,Loss_G: 4.694936752319336 ,D(x): 0.8239177465438843 ,D(G(z)) 1.1963539129877998\n",
      "epoch: 6 ,i: 500 ,Loss_D: 0.22814027965068817 ,Loss_G: 6.5727667808532715 ,D(x): 0.9865810871124268 ,D(G(z)) 66.80969690876137\n",
      "epoch: 6 ,i: 550 ,Loss_D: 0.2635767459869385 ,Loss_G: 5.850339889526367 ,D(x): 0.986315906047821 ,D(G(z)) 40.93574576830456\n",
      "epoch: 6 ,i: 600 ,Loss_D: 0.47127771377563477 ,Loss_G: 7.942336082458496 ,D(x): 0.9615585207939148 ,D(G(z)) 422.24051624930394\n",
      "epoch: 6 ,i: 650 ,Loss_D: 0.3091360926628113 ,Loss_G: 4.226832866668701 ,D(x): 0.98044353723526 ,D(G(z)) 8.37312836175999\n",
      "epoch: 6 ,i: 700 ,Loss_D: 0.18645480275154114 ,Loss_G: 4.525997638702393 ,D(x): 0.9127930402755737 ,D(G(z)) 5.004588283699999\n",
      "epoch: 6 ,i: 750 ,Loss_D: 0.1878626048564911 ,Loss_G: 2.536919116973877 ,D(x): 0.8960001468658447 ,D(G(z)) 0.3941096424742906\n",
      "epoch: 7 ,i: 0 ,Loss_D: 0.24177345633506775 ,Loss_G: 2.70499849319458 ,D(x): 0.8304775357246399 ,D(G(z)) 0.14663917573406776\n",
      "epoch: 7 ,i: 50 ,Loss_D: 0.2880169451236725 ,Loss_G: 6.752685070037842 ,D(x): 0.9893999099731445 ,D(G(z)) 98.49982089375378\n",
      "epoch: 7 ,i: 100 ,Loss_D: 0.22546330094337463 ,Loss_G: 5.908320426940918 ,D(x): 0.9764310121536255 ,D(G(z)) 37.20750523036763\n",
      "epoch: 7 ,i: 150 ,Loss_D: 0.29374420642852783 ,Loss_G: 4.624692916870117 ,D(x): 0.7811381816864014 ,D(G(z)) 0.2909032818107027\n",
      "epoch: 7 ,i: 200 ,Loss_D: 0.8042064309120178 ,Loss_G: 4.954567909240723 ,D(x): 0.8454712629318237 ,D(G(z)) 34.02611646992486\n",
      "epoch: 7 ,i: 250 ,Loss_D: 0.19658733904361725 ,Loss_G: 4.188612461090088 ,D(x): 0.8516870737075806 ,D(G(z)) 0.682123720133944\n",
      "epoch: 7 ,i: 300 ,Loss_D: 0.06658806651830673 ,Loss_G: 3.2231240272521973 ,D(x): 0.986997127532959 ,D(G(z)) 0.5685471560463267\n",
      "epoch: 7 ,i: 350 ,Loss_D: 0.2971491813659668 ,Loss_G: 3.5649752616882324 ,D(x): 0.7882187366485596 ,D(G(z)) 0.7368323118700169\n",
      "epoch: 7 ,i: 400 ,Loss_D: 0.1331142783164978 ,Loss_G: 5.640120029449463 ,D(x): 0.8907313942909241 ,D(G(z)) 0.6753105978808356\n",
      "epoch: 7 ,i: 450 ,Loss_D: 0.7186664938926697 ,Loss_G: 4.655484199523926 ,D(x): 0.564355731010437 ,D(G(z)) 0.12880180589014653\n",
      "epoch: 7 ,i: 500 ,Loss_D: 0.08644749224185944 ,Loss_G: 6.577630519866943 ,D(x): 0.9771550893783569 ,D(G(z)) 15.522774818857819\n",
      "epoch: 7 ,i: 550 ,Loss_D: 0.8802261352539062 ,Loss_G: 10.124439239501953 ,D(x): 0.9822210669517517 ,D(G(z)) 4057.998971590147\n",
      "epoch: 7 ,i: 600 ,Loss_D: 0.23202642798423767 ,Loss_G: 4.947486400604248 ,D(x): 0.9681415557861328 ,D(G(z)) 13.759843356676317\n",
      "epoch: 7 ,i: 650 ,Loss_D: 0.1774100810289383 ,Loss_G: 4.920145511627197 ,D(x): 0.8585970401763916 ,D(G(z)) 0.649856250037433\n",
      "epoch: 7 ,i: 700 ,Loss_D: 0.18564936518669128 ,Loss_G: 5.162047386169434 ,D(x): 0.9662382006645203 ,D(G(z)) 13.756091634413243\n",
      "epoch: 7 ,i: 750 ,Loss_D: 0.08841564506292343 ,Loss_G: 5.172885894775391 ,D(x): 0.9879263043403625 ,D(G(z)) 7.965919652426273\n",
      "epoch: 8 ,i: 0 ,Loss_D: 0.30499267578125 ,Loss_G: 4.482040882110596 ,D(x): 0.7794921398162842 ,D(G(z)) 0.437594744692971\n",
      "epoch: 8 ,i: 50 ,Loss_D: 0.07550343126058578 ,Loss_G: 4.170251846313477 ,D(x): 0.9617747068405151 ,D(G(z)) 1.210610272709062\n",
      "epoch: 8 ,i: 100 ,Loss_D: 0.1509391814470291 ,Loss_G: 4.968820571899414 ,D(x): 0.9612038135528564 ,D(G(z)) 9.685952126153621\n",
      "epoch: 8 ,i: 150 ,Loss_D: 0.2768835723400116 ,Loss_G: 4.282812118530273 ,D(x): 0.7874093055725098 ,D(G(z)) 0.26991259334631024\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 8 ,i: 200 ,Loss_D: 0.1575116217136383 ,Loss_G: 4.942133903503418 ,D(x): 0.9564962387084961 ,D(G(z)) 8.151028511830713\n",
      "epoch: 8 ,i: 250 ,Loss_D: 0.5941537022590637 ,Loss_G: 4.464504718780518 ,D(x): 0.8868168592453003 ,D(G(z)) 12.345497256720693\n",
      "epoch: 8 ,i: 300 ,Loss_D: 0.2680426239967346 ,Loss_G: 4.075751304626465 ,D(x): 0.8761919736862183 ,D(G(z)) 3.3738727128596993\n",
      "epoch: 8 ,i: 350 ,Loss_D: 0.1586490273475647 ,Loss_G: 3.6867055892944336 ,D(x): 0.9199986457824707 ,D(G(z)) 1.8155015330494406\n",
      "epoch: 8 ,i: 400 ,Loss_D: 0.5300279855728149 ,Loss_G: 3.1973652839660645 ,D(x): 0.6511525511741638 ,D(G(z)) 0.2629748612713142\n",
      "epoch: 8 ,i: 450 ,Loss_D: 0.3217988610267639 ,Loss_G: 5.6827287673950195 ,D(x): 0.966855525970459 ,D(G(z)) 36.93506004860836\n",
      "epoch: 8 ,i: 500 ,Loss_D: 0.4852369427680969 ,Loss_G: 3.707622528076172 ,D(x): 0.7318561673164368 ,D(G(z)) 1.9694998422483943\n",
      "epoch: 8 ,i: 550 ,Loss_D: 0.10797174274921417 ,Loss_G: 4.278679847717285 ,D(x): 0.9313133955001831 ,D(G(z)) 1.2400292312077126\n",
      "epoch: 8 ,i: 600 ,Loss_D: 0.27849555015563965 ,Loss_G: 6.377103805541992 ,D(x): 0.9743080735206604 ,D(G(z)) 76.90053255092982\n",
      "epoch: 8 ,i: 650 ,Loss_D: 0.683547854423523 ,Loss_G: 8.771289825439453 ,D(x): 0.9965471029281616 ,D(G(z)) 1496.307069010791\n",
      "epoch: 8 ,i: 700 ,Loss_D: 0.23615103960037231 ,Loss_G: 5.699212074279785 ,D(x): 0.9940975904464722 ,D(G(z)) 36.63860748295392\n",
      "epoch: 8 ,i: 750 ,Loss_D: 0.023869812488555908 ,Loss_G: 5.509256362915039 ,D(x): 0.9851218461990356 ,D(G(z)) 1.2348834343315565\n",
      "epoch: 9 ,i: 0 ,Loss_D: 0.7651240825653076 ,Loss_G: 10.79406452178955 ,D(x): 0.985387921333313 ,D(G(z)) 6513.077265352357\n",
      "epoch: 9 ,i: 50 ,Loss_D: 0.30885398387908936 ,Loss_G: 7.477386474609375 ,D(x): 0.9868674278259277 ,D(G(z)) 184.05898122585782\n",
      "epoch: 9 ,i: 100 ,Loss_D: 0.13120317459106445 ,Loss_G: 4.006467819213867 ,D(x): 0.9359110593795776 ,D(G(z)) 1.9239899003453167\n",
      "epoch: 9 ,i: 150 ,Loss_D: 0.07321959733963013 ,Loss_G: 4.212647438049316 ,D(x): 0.9452036619186401 ,D(G(z)) 0.4374616282895875\n",
      "epoch: 9 ,i: 200 ,Loss_D: 2.4509379863739014 ,Loss_G: 12.165964126586914 ,D(x): 0.9998195171356201 ,D(G(z)) 22556.490050100412\n",
      "epoch: 9 ,i: 250 ,Loss_D: 0.32541897892951965 ,Loss_G: 6.192820072174072 ,D(x): 0.9611489772796631 ,D(G(z)) 54.95754107237131\n",
      "epoch: 9 ,i: 300 ,Loss_D: 0.1546395719051361 ,Loss_G: 3.6729044914245605 ,D(x): 0.881708025932312 ,D(G(z)) 0.2811797392086577\n",
      "epoch: 9 ,i: 350 ,Loss_D: 0.22804972529411316 ,Loss_G: 2.8605947494506836 ,D(x): 0.8321335315704346 ,D(G(z)) 0.2735764604734975\n",
      "epoch: 9 ,i: 400 ,Loss_D: 0.16819065809249878 ,Loss_G: 4.938870906829834 ,D(x): 0.9936538934707642 ,D(G(z)) 13.376773934624111\n",
      "epoch: 9 ,i: 450 ,Loss_D: 0.3103746175765991 ,Loss_G: 3.7201364040374756 ,D(x): 0.7850838899612427 ,D(G(z)) 0.5048145009088851\n",
      "epoch: 9 ,i: 500 ,Loss_D: 1.39750075340271 ,Loss_G: 14.00536060333252 ,D(x): 0.9972554445266724 ,D(G(z)) 300303.2546979921\n",
      "epoch: 9 ,i: 550 ,Loss_D: 0.8808193802833557 ,Loss_G: 4.694631576538086 ,D(x): 0.4852691888809204 ,D(G(z)) 0.04920545878103312\n",
      "epoch: 9 ,i: 600 ,Loss_D: 0.0254928320646286 ,Loss_G: 3.7892208099365234 ,D(x): 0.9886212348937988 ,D(G(z)) 0.30821692356320646\n",
      "epoch: 9 ,i: 650 ,Loss_D: 0.37256166338920593 ,Loss_G: 7.3200602531433105 ,D(x): 0.9881206750869751 ,D(G(z)) 223.28761656356946\n",
      "epoch: 9 ,i: 700 ,Loss_D: 1.9241210222244263 ,Loss_G: 14.606550216674805 ,D(x): 0.9995646476745605 ,D(G(z)) 416772.13252345525\n",
      "epoch: 9 ,i: 750 ,Loss_D: 0.24107079207897186 ,Loss_G: 4.417898654937744 ,D(x): 0.815556526184082 ,D(G(z)) 0.169553519888936\n",
      "epoch: 10 ,i: 0 ,Loss_D: 0.15320663154125214 ,Loss_G: 5.100284099578857 ,D(x): 0.8861878514289856 ,D(G(z)) 1.1217235577896048\n",
      "epoch: 10 ,i: 50 ,Loss_D: 0.20919306576251984 ,Loss_G: 5.639480113983154 ,D(x): 0.957355797290802 ,D(G(z)) 23.06646914467911\n",
      "epoch: 10 ,i: 100 ,Loss_D: 0.04339855909347534 ,Loss_G: 5.014699459075928 ,D(x): 0.9772244691848755 ,D(G(z)) 0.971766188561025\n",
      "epoch: 10 ,i: 150 ,Loss_D: 0.16691473126411438 ,Loss_G: 4.733798027038574 ,D(x): 0.9294507503509521 ,D(G(z)) 4.92619492994896\n",
      "epoch: 10 ,i: 200 ,Loss_D: 0.08089809119701385 ,Loss_G: 4.375075340270996 ,D(x): 0.9618534445762634 ,D(G(z)) 1.7963933296463839\n",
      "epoch: 10 ,i: 250 ,Loss_D: 0.2670542597770691 ,Loss_G: 3.3656415939331055 ,D(x): 0.8442115783691406 ,D(G(z)) 0.8641958910356784\n",
      "epoch: 10 ,i: 300 ,Loss_D: 0.32380568981170654 ,Loss_G: 6.698144912719727 ,D(x): 0.7651848793029785 ,D(G(z)) 1.120343934901994\n",
      "epoch: 10 ,i: 350 ,Loss_D: 0.11575351655483246 ,Loss_G: 4.837551116943359 ,D(x): 0.9287824034690857 ,D(G(z)) 2.347439484560527\n",
      "epoch: 10 ,i: 400 ,Loss_D: 0.1132073923945427 ,Loss_G: 3.7665905952453613 ,D(x): 0.915283203125 ,D(G(z)) 0.4304651222928327\n",
      "epoch: 10 ,i: 450 ,Loss_D: 0.2986127734184265 ,Loss_G: 4.306379318237305 ,D(x): 0.8292312026023865 ,D(G(z)) 1.8195188964199032\n",
      "epoch: 10 ,i: 500 ,Loss_D: 0.14154599606990814 ,Loss_G: 3.266345977783203 ,D(x): 0.9986398220062256 ,D(G(z)) 2.0337499213232797\n",
      "epoch: 10 ,i: 550 ,Loss_D: 0.24126413464546204 ,Loss_G: 4.525162696838379 ,D(x): 0.9638149738311768 ,D(G(z)) 4.952533059373044\n",
      "epoch: 10 ,i: 600 ,Loss_D: 0.17191588878631592 ,Loss_G: 5.208569526672363 ,D(x): 0.9608034491539001 ,D(G(z)) 11.840683994868083\n",
      "epoch: 10 ,i: 650 ,Loss_D: 0.3764147460460663 ,Loss_G: 4.501049041748047 ,D(x): 0.7398133873939514 ,D(G(z)) 0.23526249908421284\n",
      "epoch: 10 ,i: 700 ,Loss_D: 0.14224055409431458 ,Loss_G: 4.1472883224487305 ,D(x): 0.9186218976974487 ,D(G(z)) 1.5728440301265625\n",
      "epoch: 10 ,i: 750 ,Loss_D: 0.10334441065788269 ,Loss_G: 6.027735710144043 ,D(x): 0.9830031991004944 ,D(G(z)) 18.74955396161542\n",
      "epoch: 11 ,i: 0 ,Loss_D: 0.21255463361740112 ,Loss_G: 6.901482582092285 ,D(x): 0.9967079162597656 ,D(G(z)) 97.03749616378276\n",
      "epoch: 11 ,i: 50 ,Loss_D: 0.2743707001209259 ,Loss_G: 3.910867691040039 ,D(x): 0.8754817247390747 ,D(G(z)) 2.8282949384114677\n",
      "epoch: 11 ,i: 100 ,Loss_D: 0.32109758257865906 ,Loss_G: 3.680250644683838 ,D(x): 0.7688950896263123 ,D(G(z)) 0.13124344004353028\n",
      "epoch: 11 ,i: 150 ,Loss_D: 0.04254142940044403 ,Loss_G: 4.391449451446533 ,D(x): 0.9784486293792725 ,D(G(z)) 0.9029664716576051\n",
      "epoch: 11 ,i: 200 ,Loss_D: 0.3963674306869507 ,Loss_G: 2.9032418727874756 ,D(x): 0.7796988487243652 ,D(G(z)) 0.6460130078763041\n",
      "epoch: 11 ,i: 250 ,Loss_D: 0.15091243386268616 ,Loss_G: 4.3054986000061035 ,D(x): 0.9343211650848389 ,D(G(z)) 3.2022900738664632\n",
      "epoch: 11 ,i: 300 ,Loss_D: 0.2515590786933899 ,Loss_G: 6.876338958740234 ,D(x): 0.9958533644676208 ,D(G(z)) 99.7802422332788\n",
      "epoch: 11 ,i: 350 ,Loss_D: 0.06266337633132935 ,Loss_G: 6.015723705291748 ,D(x): 0.9814592003822327 ,D(G(z)) 8.859857940103502\n",
      "epoch: 11 ,i: 400 ,Loss_D: 0.11133211106061935 ,Loss_G: 4.559858322143555 ,D(x): 0.9461678266525269 ,D(G(z)) 2.559130721909375\n",
      "epoch: 11 ,i: 450 ,Loss_D: 0.4372486472129822 ,Loss_G: 7.110215187072754 ,D(x): 0.9746391177177429 ,D(G(z)) 189.43077972505395\n",
      "epoch: 11 ,i: 500 ,Loss_D: 0.120003841817379 ,Loss_G: 4.897505760192871 ,D(x): 0.9375596046447754 ,D(G(z)) 2.995934885039653\n",
      "epoch: 11 ,i: 550 ,Loss_D: 0.3220820128917694 ,Loss_G: 4.940646171569824 ,D(x): 0.9904581904411316 ,D(G(z)) 6.805939175204908\n",
      "epoch: 11 ,i: 600 ,Loss_D: 0.18468400835990906 ,Loss_G: 4.988890171051025 ,D(x): 0.9287880659103394 ,D(G(z)) 6.916625494586057\n",
      "epoch: 11 ,i: 650 ,Loss_D: 0.40857455134391785 ,Loss_G: 8.662699699401855 ,D(x): 0.9959728717803955 ,D(G(z)) 874.616985119119\n",
      "epoch: 11 ,i: 700 ,Loss_D: 0.460470050573349 ,Loss_G: 6.178212642669678 ,D(x): 0.9683655500411987 ,D(G(z)) 53.142932600586306\n",
      "epoch: 11 ,i: 750 ,Loss_D: 0.20328301191329956 ,Loss_G: 3.845587968826294 ,D(x): 0.8835387229919434 ,D(G(z)) 1.7614118833302288\n",
      "epoch: 12 ,i: 0 ,Loss_D: 0.1982593685388565 ,Loss_G: 6.470890998840332 ,D(x): 0.9827046394348145 ,D(G(z)) 44.984982982359206\n",
      "epoch: 12 ,i: 50 ,Loss_D: 0.15270553529262543 ,Loss_G: 5.685020446777344 ,D(x): 0.954462468624115 ,D(G(z)) 13.663601209205037\n",
      "epoch: 12 ,i: 100 ,Loss_D: 0.07916225492954254 ,Loss_G: 6.62890625 ,D(x): 0.9506983757019043 ,D(G(z)) 6.495559388820305\n",
      "epoch: 12 ,i: 150 ,Loss_D: 0.0947873517870903 ,Loss_G: 5.407276153564453 ,D(x): 0.9675772786140442 ,D(G(z)) 6.882688159087352\n",
      "epoch: 12 ,i: 200 ,Loss_D: 0.08857657015323639 ,Loss_G: 5.231967926025391 ,D(x): 0.9654229283332825 ,D(G(z)) 3.9916202942753154\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 12 ,i: 250 ,Loss_D: 0.051738232374191284 ,Loss_G: 5.675075054168701 ,D(x): 0.9638148546218872 ,D(G(z)) 1.7587612933472259\n",
      "epoch: 12 ,i: 300 ,Loss_D: 0.9983354210853577 ,Loss_G: 5.842824935913086 ,D(x): 0.4795134365558624 ,D(G(z)) 0.019572602921374766\n",
      "epoch: 12 ,i: 350 ,Loss_D: 0.18076743185520172 ,Loss_G: 7.796800136566162 ,D(x): 0.9873526096343994 ,D(G(z)) 234.05409696988497\n",
      "epoch: 12 ,i: 400 ,Loss_D: 0.4240676760673523 ,Loss_G: 2.806303024291992 ,D(x): 0.7636861205101013 ,D(G(z)) 0.38641266499544125\n",
      "epoch: 12 ,i: 450 ,Loss_D: 0.19492419064044952 ,Loss_G: 3.6951119899749756 ,D(x): 0.9884425401687622 ,D(G(z)) 3.0841170524828745\n",
      "epoch: 12 ,i: 500 ,Loss_D: 0.09391738474369049 ,Loss_G: 5.645723342895508 ,D(x): 0.9603620171546936 ,D(G(z)) 6.70932856183757\n",
      "epoch: 12 ,i: 550 ,Loss_D: 0.09860657155513763 ,Loss_G: 4.267679214477539 ,D(x): 0.952228307723999 ,D(G(z)) 1.7904399939868818\n",
      "epoch: 12 ,i: 600 ,Loss_D: 0.3772949278354645 ,Loss_G: 8.176741600036621 ,D(x): 0.997809886932373 ,D(G(z)) 604.1302881500221\n",
      "epoch: 12 ,i: 650 ,Loss_D: 0.17691609263420105 ,Loss_G: 4.269145965576172 ,D(x): 0.9110094308853149 ,D(G(z)) 2.39289044058925\n",
      "epoch: 12 ,i: 700 ,Loss_D: 0.09509933739900589 ,Loss_G: 4.538912773132324 ,D(x): 0.9599902629852295 ,D(G(z)) 2.0410649982037254\n",
      "epoch: 12 ,i: 750 ,Loss_D: 1.0254056453704834 ,Loss_G: 7.71003532409668 ,D(x): 0.9782834649085999 ,D(G(z)) 231.93616657313106\n",
      "epoch: 13 ,i: 0 ,Loss_D: 0.41773805022239685 ,Loss_G: 8.707423210144043 ,D(x): 0.9962239265441895 ,D(G(z)) 626.4634538377229\n",
      "epoch: 13 ,i: 50 ,Loss_D: 0.23416997492313385 ,Loss_G: 7.820812225341797 ,D(x): 0.8174951672554016 ,D(G(z)) 0.8502237908938411\n",
      "epoch: 13 ,i: 100 ,Loss_D: 0.1754572093486786 ,Loss_G: 3.407900810241699 ,D(x): 0.876484751701355 ,D(G(z)) 0.4179838772635316\n",
      "epoch: 13 ,i: 150 ,Loss_D: 1.5519890785217285 ,Loss_G: 10.555120468139648 ,D(x): 0.9997715353965759 ,D(G(z)) 9081.34233648104\n",
      "epoch: 13 ,i: 200 ,Loss_D: 0.13787735998630524 ,Loss_G: 4.235125541687012 ,D(x): 0.9119856357574463 ,D(G(z)) 1.1722632187067938\n",
      "epoch: 13 ,i: 250 ,Loss_D: 5.509608268737793 ,Loss_G: 0.8736675977706909 ,D(x): 0.012849580496549606 ,D(G(z)) 7.533416503041541e-06\n",
      "epoch: 13 ,i: 300 ,Loss_D: 0.19590502977371216 ,Loss_G: 3.4157238006591797 ,D(x): 0.864948034286499 ,D(G(z)) 0.5704096391388842\n",
      "epoch: 13 ,i: 350 ,Loss_D: 0.32670217752456665 ,Loss_G: 4.124720573425293 ,D(x): 0.9322504997253418 ,D(G(z)) 5.755017120507577\n",
      "epoch: 13 ,i: 400 ,Loss_D: 1.3392454385757446 ,Loss_G: 7.502200126647949 ,D(x): 0.9938650131225586 ,D(G(z)) 307.0599230445565\n",
      "epoch: 13 ,i: 450 ,Loss_D: 0.14027252793312073 ,Loss_G: 4.219825744628906 ,D(x): 0.9272190928459167 ,D(G(z)) 2.0049590645368567\n",
      "epoch: 13 ,i: 500 ,Loss_D: 0.20732581615447998 ,Loss_G: 3.253875970840454 ,D(x): 0.8726577758789062 ,D(G(z)) 0.6565058562535484\n",
      "epoch: 13 ,i: 550 ,Loss_D: 0.16638648509979248 ,Loss_G: 4.957311153411865 ,D(x): 0.9251657724380493 ,D(G(z)) 5.2721812299485125\n",
      "epoch: 13 ,i: 600 ,Loss_D: 0.1485937535762787 ,Loss_G: 3.8174099922180176 ,D(x): 0.8942110538482666 ,D(G(z)) 0.38692219023192326\n",
      "epoch: 13 ,i: 650 ,Loss_D: 0.24093952775001526 ,Loss_G: 3.2542567253112793 ,D(x): 0.8368855714797974 ,D(G(z)) 0.17841643261089693\n",
      "epoch: 13 ,i: 700 ,Loss_D: 0.053875889629125595 ,Loss_G: 4.750732898712158 ,D(x): 0.960504412651062 ,D(G(z)) 0.6622023345008987\n",
      "epoch: 13 ,i: 750 ,Loss_D: 0.1533527672290802 ,Loss_G: 6.487837314605713 ,D(x): 0.9697669148445129 ,D(G(z)) 18.422083786758336\n",
      "epoch: 14 ,i: 0 ,Loss_D: 0.10348247736692429 ,Loss_G: 3.4414639472961426 ,D(x): 0.9869118928909302 ,D(G(z)) 1.3622153094975098\n",
      "epoch: 14 ,i: 50 ,Loss_D: 0.4021894931793213 ,Loss_G: 8.162910461425781 ,D(x): 0.962317705154419 ,D(G(z)) 317.1232197806475\n",
      "epoch: 14 ,i: 100 ,Loss_D: 2.5974807739257812 ,Loss_G: 16.278697967529297 ,D(x): 0.9998548626899719 ,D(G(z)) 2861951.4203711143\n",
      "epoch: 14 ,i: 150 ,Loss_D: 1.000051498413086 ,Loss_G: 8.565940856933594 ,D(x): 0.9978664517402649 ,D(G(z)) 409.5559511338004\n",
      "epoch: 14 ,i: 200 ,Loss_D: 0.270350843667984 ,Loss_G: 3.303524971008301 ,D(x): 0.9960559606552124 ,D(G(z)) 3.327663808255711\n",
      "epoch: 14 ,i: 250 ,Loss_D: 0.2863294184207916 ,Loss_G: 5.462376594543457 ,D(x): 0.9917812347412109 ,D(G(z)) 24.284426251283538\n",
      "epoch: 14 ,i: 300 ,Loss_D: 0.16225573420524597 ,Loss_G: 5.1551055908203125 ,D(x): 0.9521654844284058 ,D(G(z)) 7.956575166446691\n",
      "epoch: 14 ,i: 350 ,Loss_D: 0.09890150278806686 ,Loss_G: 5.249897003173828 ,D(x): 0.9849578142166138 ,D(G(z)) 11.157392968373363\n",
      "epoch: 14 ,i: 400 ,Loss_D: 0.1904434710741043 ,Loss_G: 4.020061492919922 ,D(x): 0.847904622554779 ,D(G(z)) 0.041227728313655516\n",
      "epoch: 14 ,i: 450 ,Loss_D: 2.5680534839630127 ,Loss_G: 15.793293952941895 ,D(x): 0.9998455047607422 ,D(G(z)) 447091.28590895026\n",
      "epoch: 14 ,i: 500 ,Loss_D: 0.1487727016210556 ,Loss_G: 4.026976585388184 ,D(x): 0.917712926864624 ,D(G(z)) 1.0084754242475038\n",
      "epoch: 14 ,i: 550 ,Loss_D: 0.0921034887433052 ,Loss_G: 4.992198944091797 ,D(x): 0.9333349466323853 ,D(G(z)) 1.1277584368108573\n",
      "epoch: 14 ,i: 600 ,Loss_D: 0.8040737509727478 ,Loss_G: 3.017910957336426 ,D(x): 0.5549749732017517 ,D(G(z)) 0.057512468424868506\n",
      "epoch: 14 ,i: 650 ,Loss_D: 0.4215755760669708 ,Loss_G: 8.04359245300293 ,D(x): 0.9843430519104004 ,D(G(z)) 399.3315231071622\n",
      "epoch: 14 ,i: 700 ,Loss_D: 0.06858304888010025 ,Loss_G: 5.497467041015625 ,D(x): 0.9475452899932861 ,D(G(z)) 0.9398768443807157\n",
      "epoch: 14 ,i: 750 ,Loss_D: 0.1642899215221405 ,Loss_G: 5.2306413650512695 ,D(x): 0.9768903255462646 ,D(G(z)) 14.867504519442464\n",
      "epoch: 15 ,i: 0 ,Loss_D: 0.10893505066633224 ,Loss_G: 4.778785705566406 ,D(x): 0.9809715747833252 ,D(G(z)) 3.024591533041788\n",
      "epoch: 15 ,i: 50 ,Loss_D: 0.04081945866346359 ,Loss_G: 4.122608661651611 ,D(x): 0.9788584113121033 ,D(G(z)) 0.6193486704704837\n",
      "epoch: 15 ,i: 100 ,Loss_D: 0.08796970546245575 ,Loss_G: 5.00812292098999 ,D(x): 0.9618839025497437 ,D(G(z)) 3.842256811968274\n",
      "epoch: 15 ,i: 150 ,Loss_D: 0.06959797441959381 ,Loss_G: 5.173038482666016 ,D(x): 0.9857786893844604 ,D(G(z)) 5.818758745954041\n",
      "epoch: 15 ,i: 200 ,Loss_D: 0.09605534374713898 ,Loss_G: 4.620784759521484 ,D(x): 0.9559532403945923 ,D(G(z)) 2.320190614834648\n",
      "epoch: 15 ,i: 250 ,Loss_D: 0.07478095591068268 ,Loss_G: 5.422201156616211 ,D(x): 0.9768534898757935 ,D(G(z)) 4.158238689647052\n",
      "epoch: 15 ,i: 300 ,Loss_D: 0.7845366597175598 ,Loss_G: 4.358397483825684 ,D(x): 0.5479955673217773 ,D(G(z)) 0.23865137442153872\n",
      "epoch: 15 ,i: 350 ,Loss_D: 0.7403552532196045 ,Loss_G: 3.025322437286377 ,D(x): 0.5635054111480713 ,D(G(z)) 0.011059380722326831\n",
      "epoch: 15 ,i: 400 ,Loss_D: 0.21686774492263794 ,Loss_G: 3.985924005508423 ,D(x): 0.9765388369560242 ,D(G(z)) 4.509805087907647\n",
      "epoch: 15 ,i: 450 ,Loss_D: 0.18705493211746216 ,Loss_G: 2.6111013889312744 ,D(x): 0.8634669780731201 ,D(G(z)) 0.17531935911177599\n",
      "epoch: 15 ,i: 500 ,Loss_D: 0.15370219945907593 ,Loss_G: 4.087765216827393 ,D(x): 0.918194055557251 ,D(G(z)) 1.6503651411642972\n",
      "epoch: 15 ,i: 550 ,Loss_D: 0.1615675389766693 ,Loss_G: 5.602655410766602 ,D(x): 0.9952212572097778 ,D(G(z)) 16.898478748263074\n",
      "epoch: 15 ,i: 600 ,Loss_D: 0.07363045960664749 ,Loss_G: 7.638486862182617 ,D(x): 0.9405175447463989 ,D(G(z)) 6.475894966906468\n",
      "epoch: 15 ,i: 650 ,Loss_D: 0.07487702369689941 ,Loss_G: 4.694250106811523 ,D(x): 0.9819353222846985 ,D(G(z)) 2.9224212499098967\n",
      "epoch: 15 ,i: 700 ,Loss_D: 0.1374492645263672 ,Loss_G: 5.360509395599365 ,D(x): 0.9709047079086304 ,D(G(z)) 9.292054717163673\n",
      "epoch: 15 ,i: 750 ,Loss_D: 0.06859219819307327 ,Loss_G: 4.753376483917236 ,D(x): 0.9663952589035034 ,D(G(z)) 2.170731729952838\n",
      "epoch: 16 ,i: 0 ,Loss_D: 0.12681172788143158 ,Loss_G: 4.863142490386963 ,D(x): 0.8971368670463562 ,D(G(z)) 0.27174616949288577\n",
      "epoch: 16 ,i: 50 ,Loss_D: 2.35054349899292 ,Loss_G: 1.2105584144592285 ,D(x): 0.17328718304634094 ,D(G(z)) 0.0005083858930519681\n",
      "epoch: 16 ,i: 100 ,Loss_D: 0.45034998655319214 ,Loss_G: 1.339737892150879 ,D(x): 0.7197577953338623 ,D(G(z)) 0.05335439719170134\n",
      "epoch: 16 ,i: 150 ,Loss_D: 0.1916634440422058 ,Loss_G: 2.9807095527648926 ,D(x): 0.887993335723877 ,D(G(z)) 0.4531457632605258\n",
      "epoch: 16 ,i: 200 ,Loss_D: 0.20109719038009644 ,Loss_G: 6.401035308837891 ,D(x): 0.9950497150421143 ,D(G(z)) 53.711610090850066\n",
      "epoch: 16 ,i: 250 ,Loss_D: 0.16198214888572693 ,Loss_G: 5.007796287536621 ,D(x): 0.9898102283477783 ,D(G(z)) 8.944377555713045\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 16 ,i: 300 ,Loss_D: 0.07641364634037018 ,Loss_G: 4.47475004196167 ,D(x): 0.9443472623825073 ,D(G(z)) 0.7144794016736314\n",
      "epoch: 16 ,i: 350 ,Loss_D: 0.15691934525966644 ,Loss_G: 8.342599868774414 ,D(x): 0.8747706413269043 ,D(G(z)) 2.493461865101985\n",
      "epoch: 16 ,i: 400 ,Loss_D: 0.27222949266433716 ,Loss_G: 9.492829322814941 ,D(x): 0.9967358112335205 ,D(G(z)) 986.8474230930161\n",
      "epoch: 16 ,i: 450 ,Loss_D: 0.21893256902694702 ,Loss_G: 4.147974967956543 ,D(x): 0.8512954711914062 ,D(G(z)) 0.6339430539119502\n",
      "epoch: 16 ,i: 500 ,Loss_D: 0.06393196433782578 ,Loss_G: 5.030337333679199 ,D(x): 0.9900944828987122 ,D(G(z)) 4.62733065217704\n",
      "epoch: 16 ,i: 550 ,Loss_D: 0.3458530008792877 ,Loss_G: 3.728313684463501 ,D(x): 0.8321247696876526 ,D(G(z)) 1.0098765248848054\n",
      "epoch: 16 ,i: 600 ,Loss_D: 0.3403463661670685 ,Loss_G: 2.7130823135375977 ,D(x): 0.7760624885559082 ,D(G(z)) 0.07529449679220628\n",
      "epoch: 16 ,i: 650 ,Loss_D: 0.11288762092590332 ,Loss_G: 4.453307628631592 ,D(x): 0.9680961966514587 ,D(G(z)) 2.8688485734170506\n",
      "epoch: 16 ,i: 700 ,Loss_D: 0.06698311865329742 ,Loss_G: 5.290999889373779 ,D(x): 0.9604792594909668 ,D(G(z)) 1.8430417767064764\n",
      "epoch: 16 ,i: 750 ,Loss_D: 0.10141052305698395 ,Loss_G: 4.931937217712402 ,D(x): 0.9295704364776611 ,D(G(z)) 1.2796433857229879\n",
      "epoch: 17 ,i: 0 ,Loss_D: 0.10113207250833511 ,Loss_G: 5.894789695739746 ,D(x): 0.9870897531509399 ,D(G(z)) 15.846019474817485\n",
      "epoch: 17 ,i: 50 ,Loss_D: 0.28341856598854065 ,Loss_G: 4.973891258239746 ,D(x): 0.9837867021560669 ,D(G(z)) 10.21508597999282\n",
      "epoch: 17 ,i: 100 ,Loss_D: 0.20274312794208527 ,Loss_G: 4.055000305175781 ,D(x): 0.8513998985290527 ,D(G(z)) 0.5227738204328443\n",
      "epoch: 17 ,i: 150 ,Loss_D: 0.0492035448551178 ,Loss_G: 6.928011417388916 ,D(x): 0.9565585255622864 ,D(G(z)) 1.0123800318302645\n",
      "epoch: 17 ,i: 200 ,Loss_D: 0.10212026536464691 ,Loss_G: 5.175654411315918 ,D(x): 0.9246654510498047 ,D(G(z)) 1.2492036059614644\n",
      "epoch: 17 ,i: 250 ,Loss_D: 0.03769565373659134 ,Loss_G: 4.7053446769714355 ,D(x): 0.9854233264923096 ,D(G(z)) 1.4975138355495399\n",
      "epoch: 17 ,i: 300 ,Loss_D: 0.046355798840522766 ,Loss_G: 5.434613227844238 ,D(x): 0.9749236106872559 ,D(G(z)) 2.0321513454592997\n",
      "epoch: 17 ,i: 350 ,Loss_D: 0.21856805682182312 ,Loss_G: 8.16303825378418 ,D(x): 0.9984550476074219 ,D(G(z)) 340.6504318453272\n",
      "epoch: 17 ,i: 400 ,Loss_D: 0.08995451033115387 ,Loss_G: 5.913978576660156 ,D(x): 0.978532075881958 ,D(G(z)) 12.178143811700169\n",
      "epoch: 17 ,i: 450 ,Loss_D: 1.0552489757537842 ,Loss_G: 1.5597941875457764 ,D(x): 0.6006786823272705 ,D(G(z)) 0.3831997208966615\n",
      "epoch: 17 ,i: 500 ,Loss_D: 0.2517310380935669 ,Loss_G: 4.049252510070801 ,D(x): 0.8582366704940796 ,D(G(z)) 1.303350597310293\n",
      "epoch: 17 ,i: 550 ,Loss_D: 0.2578146457672119 ,Loss_G: 5.3613996505737305 ,D(x): 0.8402637243270874 ,D(G(z)) 2.580011397036184\n",
      "epoch: 17 ,i: 600 ,Loss_D: 0.33681637048721313 ,Loss_G: 5.9815826416015625 ,D(x): 0.9754042029380798 ,D(G(z)) 45.48925290945635\n",
      "epoch: 17 ,i: 650 ,Loss_D: 0.24243496358394623 ,Loss_G: 6.444088935852051 ,D(x): 0.9708375930786133 ,D(G(z)) 50.325657207671654\n",
      "epoch: 17 ,i: 700 ,Loss_D: 0.16057462990283966 ,Loss_G: 5.358983993530273 ,D(x): 0.9763531684875488 ,D(G(z)) 11.881414698461999\n",
      "epoch: 17 ,i: 750 ,Loss_D: 0.15857023000717163 ,Loss_G: 3.866973638534546 ,D(x): 0.9015438556671143 ,D(G(z)) 0.7966100675088033\n",
      "epoch: 18 ,i: 0 ,Loss_D: 0.04693165421485901 ,Loss_G: 5.100615501403809 ,D(x): 0.974867045879364 ,D(G(z)) 1.278553185912937\n",
      "epoch: 18 ,i: 50 ,Loss_D: 0.06829959899187088 ,Loss_G: 5.885841369628906 ,D(x): 0.9703322649002075 ,D(G(z)) 5.725343670464779\n",
      "epoch: 18 ,i: 100 ,Loss_D: 0.05025378242135048 ,Loss_G: 5.070450782775879 ,D(x): 0.9891247153282166 ,D(G(z)) 3.5806270166595855\n",
      "epoch: 18 ,i: 150 ,Loss_D: 0.1655261516571045 ,Loss_G: 4.902920722961426 ,D(x): 0.8928070068359375 ,D(G(z)) 1.6873947008380448\n",
      "epoch: 18 ,i: 200 ,Loss_D: 0.10184651613235474 ,Loss_G: 5.378731727600098 ,D(x): 0.9570069313049316 ,D(G(z)) 6.043677853525451\n",
      "epoch: 18 ,i: 250 ,Loss_D: 0.36769965291023254 ,Loss_G: 9.418403625488281 ,D(x): 0.9924521446228027 ,D(G(z)) 1698.5410539750521\n",
      "epoch: 18 ,i: 300 ,Loss_D: 0.07183802872896194 ,Loss_G: 4.808902263641357 ,D(x): 0.9824802279472351 ,D(G(z)) 2.6454564428714584\n",
      "epoch: 18 ,i: 350 ,Loss_D: 1.0870198011398315 ,Loss_G: 5.5488433837890625 ,D(x): 0.4778215289115906 ,D(G(z)) 0.008228264849903962\n",
      "epoch: 18 ,i: 400 ,Loss_D: 0.1130041629076004 ,Loss_G: 5.850656509399414 ,D(x): 0.9103097915649414 ,D(G(z)) 0.9893874488419038\n",
      "epoch: 18 ,i: 450 ,Loss_D: 0.9292078018188477 ,Loss_G: 3.5199477672576904 ,D(x): 0.5135965943336487 ,D(G(z)) 0.0029979092591441276\n",
      "epoch: 18 ,i: 500 ,Loss_D: 0.17777769267559052 ,Loss_G: 4.462878227233887 ,D(x): 0.9259710311889648 ,D(G(z)) 2.7289847836676717\n",
      "epoch: 18 ,i: 550 ,Loss_D: 0.09930746257305145 ,Loss_G: 4.581032752990723 ,D(x): 0.9237156510353088 ,D(G(z)) 0.3323567590459097\n",
      "epoch: 18 ,i: 600 ,Loss_D: 0.17434346675872803 ,Loss_G: 5.257747650146484 ,D(x): 0.897321343421936 ,D(G(z)) 1.950064595778944\n",
      "epoch: 18 ,i: 650 ,Loss_D: 0.1177406758069992 ,Loss_G: 6.78147554397583 ,D(x): 0.9924963712692261 ,D(G(z)) 30.634713755669786\n",
      "epoch: 18 ,i: 700 ,Loss_D: 0.3365705609321594 ,Loss_G: 9.111618041992188 ,D(x): 0.9967964291572571 ,D(G(z)) 1111.7864655760804\n",
      "epoch: 18 ,i: 750 ,Loss_D: 0.8402049541473389 ,Loss_G: 10.746662139892578 ,D(x): 0.9923684597015381 ,D(G(z)) 6741.6593853342965\n",
      "epoch: 19 ,i: 0 ,Loss_D: 1.3513741493225098 ,Loss_G: 13.744333267211914 ,D(x): 0.9993355870246887 ,D(G(z)) 119242.30250195503\n",
      "epoch: 19 ,i: 50 ,Loss_D: 0.16211141645908356 ,Loss_G: 7.039665222167969 ,D(x): 0.8688568472862244 ,D(G(z)) 2.3368082084299586\n",
      "epoch: 19 ,i: 100 ,Loss_D: 0.10933490097522736 ,Loss_G: 4.866926670074463 ,D(x): 0.9762448072433472 ,D(G(z)) 6.632066898350232\n",
      "epoch: 19 ,i: 150 ,Loss_D: 0.057597726583480835 ,Loss_G: 4.512500762939453 ,D(x): 0.9848017692565918 ,D(G(z)) 2.2243191883595332\n",
      "epoch: 19 ,i: 200 ,Loss_D: 0.042153649032115936 ,Loss_G: 5.097713470458984 ,D(x): 0.9844472408294678 ,D(G(z)) 2.223509468530055\n",
      "epoch: 19 ,i: 250 ,Loss_D: 0.23273052275180817 ,Loss_G: 8.601858139038086 ,D(x): 0.9985347390174866 ,D(G(z)) 454.302984746494\n",
      "epoch: 19 ,i: 300 ,Loss_D: 0.08234822750091553 ,Loss_G: 5.700776100158691 ,D(x): 0.9381348490715027 ,D(G(z)) 1.3127202129179676\n",
      "epoch: 19 ,i: 350 ,Loss_D: 0.6158735752105713 ,Loss_G: 4.4730048179626465 ,D(x): 0.6579705476760864 ,D(G(z)) 0.20643788623971307\n",
      "epoch: 19 ,i: 400 ,Loss_D: 0.2057150900363922 ,Loss_G: 5.888286590576172 ,D(x): 0.9314424991607666 ,D(G(z)) 10.678389850071605\n",
      "epoch: 19 ,i: 450 ,Loss_D: 0.12778328359127045 ,Loss_G: 4.733672142028809 ,D(x): 0.9348786473274231 ,D(G(z)) 2.2780949940621555\n",
      "epoch: 19 ,i: 500 ,Loss_D: 0.4227124750614166 ,Loss_G: 2.469104051589966 ,D(x): 0.7289568185806274 ,D(G(z)) 0.09982385595624013\n",
      "epoch: 19 ,i: 550 ,Loss_D: 0.08335882425308228 ,Loss_G: 5.074672698974609 ,D(x): 0.946602463722229 ,D(G(z)) 1.6000632698427255\n",
      "epoch: 19 ,i: 600 ,Loss_D: 0.09869793057441711 ,Loss_G: 4.271949768066406 ,D(x): 0.9275093674659729 ,D(G(z)) 0.5022422405013407\n",
      "epoch: 19 ,i: 650 ,Loss_D: 1.484670639038086 ,Loss_G: 10.86048412322998 ,D(x): 0.9863665103912354 ,D(G(z)) 9630.978179245603\n",
      "epoch: 19 ,i: 700 ,Loss_D: 0.1637876033782959 ,Loss_G: 4.534485816955566 ,D(x): 0.8845441341400146 ,D(G(z)) 1.3031148526163625\n",
      "epoch: 19 ,i: 750 ,Loss_D: 0.2301633507013321 ,Loss_G: 8.640348434448242 ,D(x): 0.9945611953735352 ,D(G(z)) 412.9798162173281\n",
      "epoch: 20 ,i: 0 ,Loss_D: 0.18328624963760376 ,Loss_G: 3.4038870334625244 ,D(x): 0.8989599943161011 ,D(G(z)) 0.9274145133080017\n",
      "epoch: 20 ,i: 50 ,Loss_D: 0.10876794159412384 ,Loss_G: 5.25181245803833 ,D(x): 0.9731103777885437 ,D(G(z)) 6.817255917238859\n",
      "epoch: 20 ,i: 100 ,Loss_D: 0.39286160469055176 ,Loss_G: 9.093803405761719 ,D(x): 0.994793713092804 ,D(G(z)) 1292.1392072493886\n",
      "epoch: 20 ,i: 150 ,Loss_D: 0.0729864239692688 ,Loss_G: 6.186578750610352 ,D(x): 0.9652613401412964 ,D(G(z)) 6.13709647272436\n",
      "epoch: 20 ,i: 200 ,Loss_D: 0.24669255316257477 ,Loss_G: 3.8511948585510254 ,D(x): 0.8310280442237854 ,D(G(z)) 0.17054685128527353\n",
      "epoch: 20 ,i: 250 ,Loss_D: 0.1735943853855133 ,Loss_G: 5.923460006713867 ,D(x): 0.8779178857803345 ,D(G(z)) 1.8427773582774292\n",
      "epoch: 20 ,i: 300 ,Loss_D: 0.08566711843013763 ,Loss_G: 5.252341270446777 ,D(x): 0.9592629671096802 ,D(G(z)) 3.084243628513377\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 20 ,i: 350 ,Loss_D: 0.7125941514968872 ,Loss_G: 1.8956929445266724 ,D(x): 0.6219649314880371 ,D(G(z)) 0.045611180958409596\n",
      "epoch: 20 ,i: 400 ,Loss_D: 0.09594443440437317 ,Loss_G: 5.190493583679199 ,D(x): 0.9380660057067871 ,D(G(z)) 0.9999527280561312\n",
      "epoch: 20 ,i: 450 ,Loss_D: 0.2054351568222046 ,Loss_G: 6.430739879608154 ,D(x): 0.9767086505889893 ,D(G(z)) 54.28273094947324\n",
      "epoch: 20 ,i: 500 ,Loss_D: 0.21393704414367676 ,Loss_G: 3.3520474433898926 ,D(x): 0.8634728193283081 ,D(G(z)) 0.426802368838727\n",
      "epoch: 20 ,i: 550 ,Loss_D: 0.38764792680740356 ,Loss_G: 5.514129638671875 ,D(x): 0.7306193709373474 ,D(G(z)) 0.11796238283523003\n",
      "epoch: 20 ,i: 600 ,Loss_D: 0.04957679659128189 ,Loss_G: 5.039027214050293 ,D(x): 0.985869288444519 ,D(G(z)) 2.465539779206285\n",
      "epoch: 20 ,i: 650 ,Loss_D: 0.10109160840511322 ,Loss_G: 6.519966125488281 ,D(x): 0.9261765480041504 ,D(G(z)) 3.58701046661946\n",
      "epoch: 20 ,i: 700 ,Loss_D: 0.09805241227149963 ,Loss_G: 5.05406379699707 ,D(x): 0.9733297228813171 ,D(G(z)) 5.708318006226625\n",
      "epoch: 20 ,i: 750 ,Loss_D: 0.31321921944618225 ,Loss_G: 4.765370845794678 ,D(x): 0.8895312547683716 ,D(G(z)) 5.4565837429100155\n",
      "epoch: 21 ,i: 0 ,Loss_D: 1.2037183046340942 ,Loss_G: 11.402199745178223 ,D(x): 0.9413703680038452 ,D(G(z)) 11180.81828605591\n",
      "epoch: 21 ,i: 50 ,Loss_D: 0.9959877133369446 ,Loss_G: 12.880826950073242 ,D(x): 0.9977043867111206 ,D(G(z)) 67540.1647996051\n",
      "epoch: 21 ,i: 100 ,Loss_D: 0.06933937966823578 ,Loss_G: 5.0520219802856445 ,D(x): 0.9828460812568665 ,D(G(z)) 4.460124954433748\n",
      "epoch: 21 ,i: 150 ,Loss_D: 0.11462578177452087 ,Loss_G: 5.611532211303711 ,D(x): 0.9889436960220337 ,D(G(z)) 10.073350397076478\n",
      "epoch: 21 ,i: 200 ,Loss_D: 0.14794030785560608 ,Loss_G: 5.77166748046875 ,D(x): 0.9967957735061646 ,D(G(z)) 16.802077758526906\n",
      "epoch: 21 ,i: 250 ,Loss_D: 0.05079732835292816 ,Loss_G: 4.748355865478516 ,D(x): 0.9685183763504028 ,D(G(z)) 0.7497925804771652\n",
      "epoch: 21 ,i: 300 ,Loss_D: 0.038021113723516464 ,Loss_G: 5.714207649230957 ,D(x): 0.9936420917510986 ,D(G(z)) 3.713459920158511\n",
      "epoch: 21 ,i: 350 ,Loss_D: 0.15677142143249512 ,Loss_G: 3.164219617843628 ,D(x): 0.8959158658981323 ,D(G(z)) 0.281067464286471\n",
      "epoch: 21 ,i: 400 ,Loss_D: 0.06833896785974503 ,Loss_G: 4.789546012878418 ,D(x): 0.9465615749359131 ,D(G(z)) 0.3529389320756821\n",
      "epoch: 21 ,i: 450 ,Loss_D: 0.14680270850658417 ,Loss_G: 3.113790988922119 ,D(x): 0.9075524210929871 ,D(G(z)) 0.3487102581383144\n",
      "epoch: 21 ,i: 500 ,Loss_D: 0.6011099815368652 ,Loss_G: 10.51588249206543 ,D(x): 0.9994441270828247 ,D(G(z)) 5885.763860319201\n",
      "epoch: 21 ,i: 550 ,Loss_D: 0.8622064590454102 ,Loss_G: 3.2333788871765137 ,D(x): 0.5357693433761597 ,D(G(z)) 0.0836073097718095\n",
      "epoch: 21 ,i: 600 ,Loss_D: 1.278953194618225 ,Loss_G: 1.5811705589294434 ,D(x): 0.41346466541290283 ,D(G(z)) 0.0015506216257601356\n",
      "epoch: 21 ,i: 650 ,Loss_D: 1.9824681282043457 ,Loss_G: 3.0001730918884277 ,D(x): 0.2624855041503906 ,D(G(z)) 0.0006680999803445214\n",
      "epoch: 21 ,i: 700 ,Loss_D: 0.15042456984519958 ,Loss_G: 4.506538391113281 ,D(x): 0.9393277168273926 ,D(G(z)) 3.695433295997296\n",
      "epoch: 21 ,i: 750 ,Loss_D: 0.09606628119945526 ,Loss_G: 5.267414093017578 ,D(x): 0.9567146301269531 ,D(G(z)) 3.8127926231415326\n",
      "epoch: 22 ,i: 0 ,Loss_D: 0.10669819265604019 ,Loss_G: 4.058267593383789 ,D(x): 0.927395761013031 ,D(G(z)) 0.31994547902184856\n",
      "epoch: 22 ,i: 50 ,Loss_D: 0.10335824638605118 ,Loss_G: 6.453061103820801 ,D(x): 0.9796130061149597 ,D(G(z)) 20.13289788978792\n",
      "epoch: 22 ,i: 100 ,Loss_D: 0.10380207002162933 ,Loss_G: 6.072146892547607 ,D(x): 0.9852653741836548 ,D(G(z)) 17.805169621689835\n",
      "epoch: 22 ,i: 150 ,Loss_D: 0.03641321510076523 ,Loss_G: 7.124737739562988 ,D(x): 0.9745464324951172 ,D(G(z)) 3.3916439953697073\n",
      "epoch: 22 ,i: 200 ,Loss_D: 0.297004371881485 ,Loss_G: 5.749634742736816 ,D(x): 0.9128017425537109 ,D(G(z)) 12.160643942666118\n",
      "epoch: 22 ,i: 250 ,Loss_D: 0.19871021807193756 ,Loss_G: 3.791395425796509 ,D(x): 0.8694674968719482 ,D(G(z)) 0.7297208484701498\n",
      "epoch: 22 ,i: 300 ,Loss_D: 0.05490047484636307 ,Loss_G: 5.856355667114258 ,D(x): 0.9669426083564758 ,D(G(z)) 2.208452105390059\n",
      "epoch: 22 ,i: 350 ,Loss_D: 0.08796632289886475 ,Loss_G: 4.680469512939453 ,D(x): 0.9370380640029907 ,D(G(z)) 0.9667377594247537\n",
      "epoch: 22 ,i: 400 ,Loss_D: 1.6177952289581299 ,Loss_G: 0.6794061064720154 ,D(x): 0.31051045656204224 ,D(G(z)) 0.001225757215602903\n",
      "epoch: 22 ,i: 450 ,Loss_D: 0.1977410465478897 ,Loss_G: 4.511152744293213 ,D(x): 0.8785353302955627 ,D(G(z)) 0.9650893068031746\n",
      "epoch: 22 ,i: 500 ,Loss_D: 0.06554169207811356 ,Loss_G: 5.575896739959717 ,D(x): 0.9900534152984619 ,D(G(z)) 5.813192274262713\n",
      "epoch: 22 ,i: 550 ,Loss_D: 0.11209848523139954 ,Loss_G: 4.858705520629883 ,D(x): 0.9154257774353027 ,D(G(z)) 0.4373806355678155\n",
      "epoch: 22 ,i: 600 ,Loss_D: 0.04873725399374962 ,Loss_G: 5.5915093421936035 ,D(x): 0.995483934879303 ,D(G(z)) 5.682435405368804\n",
      "epoch: 22 ,i: 650 ,Loss_D: 0.13198944926261902 ,Loss_G: 4.318391799926758 ,D(x): 0.8999853134155273 ,D(G(z)) 0.2528563700761488\n",
      "epoch: 22 ,i: 700 ,Loss_D: 0.04033556953072548 ,Loss_G: 5.956850051879883 ,D(x): 0.9700233340263367 ,D(G(z)) 0.9816712174647487\n",
      "epoch: 22 ,i: 750 ,Loss_D: 0.02939428947865963 ,Loss_G: 7.157544136047363 ,D(x): 0.9759401082992554 ,D(G(z)) 2.224365581647035\n",
      "epoch: 23 ,i: 0 ,Loss_D: 0.8309338688850403 ,Loss_G: 9.264847755432129 ,D(x): 0.9992935061454773 ,D(G(z)) 210.4305326063593\n",
      "epoch: 23 ,i: 50 ,Loss_D: 2.809370756149292 ,Loss_G: 2.9129528999328613 ,D(x): 0.14451955258846283 ,D(G(z)) 0.0006611854082759699\n",
      "epoch: 23 ,i: 100 ,Loss_D: 0.34265920519828796 ,Loss_G: 9.194474220275879 ,D(x): 0.9832793474197388 ,D(G(z)) 948.8699272379479\n",
      "epoch: 23 ,i: 150 ,Loss_D: 0.17521581053733826 ,Loss_G: 6.56160831451416 ,D(x): 0.9963318109512329 ,D(G(z)) 55.68509247219964\n",
      "epoch: 23 ,i: 200 ,Loss_D: 0.07655971497297287 ,Loss_G: 4.810552597045898 ,D(x): 0.9856158494949341 ,D(G(z)) 3.319753388854063\n",
      "epoch: 23 ,i: 250 ,Loss_D: 0.05989763140678406 ,Loss_G: 5.759020805358887 ,D(x): 0.9961990714073181 ,D(G(z)) 9.322506014067823\n",
      "epoch: 23 ,i: 300 ,Loss_D: 0.06050577014684677 ,Loss_G: 5.2147603034973145 ,D(x): 0.9618976712226868 ,D(G(z)) 1.2495854131995434\n",
      "epoch: 23 ,i: 350 ,Loss_D: 0.02513962611556053 ,Loss_G: 7.506019592285156 ,D(x): 0.9809795022010803 ,D(G(z)) 3.2590359474937283\n",
      "epoch: 23 ,i: 400 ,Loss_D: 0.10218574851751328 ,Loss_G: 3.856441020965576 ,D(x): 0.9375101923942566 ,D(G(z)) 0.3635365692650372\n",
      "epoch: 23 ,i: 450 ,Loss_D: 0.2796761393547058 ,Loss_G: 4.379322052001953 ,D(x): 0.8230054974555969 ,D(G(z)) 0.26925338182595604\n",
      "epoch: 23 ,i: 500 ,Loss_D: 0.06304243952035904 ,Loss_G: 6.067185401916504 ,D(x): 0.9854746460914612 ,D(G(z)) 7.151142216647129\n",
      "epoch: 23 ,i: 550 ,Loss_D: 5.016002655029297 ,Loss_G: 0.3698662519454956 ,D(x): 0.027203958481550217 ,D(G(z)) 0.0005778040245987635\n",
      "epoch: 23 ,i: 600 ,Loss_D: 0.16090840101242065 ,Loss_G: 5.460153579711914 ,D(x): 0.945311427116394 ,D(G(z)) 8.050806247719631\n",
      "epoch: 23 ,i: 650 ,Loss_D: 0.06591387093067169 ,Loss_G: 6.308602809906006 ,D(x): 0.988055944442749 ,D(G(z)) 10.23401569533709\n",
      "epoch: 23 ,i: 700 ,Loss_D: 0.09013794362545013 ,Loss_G: 5.702023506164551 ,D(x): 0.961641788482666 ,D(G(z)) 5.052878819213794\n",
      "epoch: 23 ,i: 750 ,Loss_D: 0.14300334453582764 ,Loss_G: 4.985018253326416 ,D(x): 0.9438459873199463 ,D(G(z)) 4.720442305735388\n",
      "epoch: 24 ,i: 0 ,Loss_D: 0.5254919528961182 ,Loss_G: 10.966988563537598 ,D(x): 0.9992140531539917 ,D(G(z)) 4787.073932095046\n",
      "epoch: 24 ,i: 50 ,Loss_D: 0.04857106879353523 ,Loss_G: 5.4517083168029785 ,D(x): 0.9940744042396545 ,D(G(z)) 3.907869819457884\n",
      "epoch: 24 ,i: 100 ,Loss_D: 0.06888437271118164 ,Loss_G: 5.047463893890381 ,D(x): 0.9530943632125854 ,D(G(z)) 1.3967090646706568\n",
      "epoch: 24 ,i: 150 ,Loss_D: 0.7398658990859985 ,Loss_G: 9.20905876159668 ,D(x): 0.999750018119812 ,D(G(z)) 887.9073055875901\n",
      "epoch: 24 ,i: 200 ,Loss_D: 0.09124913811683655 ,Loss_G: 5.5016069412231445 ,D(x): 0.979895830154419 ,D(G(z)) 8.786130197734764\n",
      "epoch: 24 ,i: 250 ,Loss_D: 0.20401176810264587 ,Loss_G: 6.0705366134643555 ,D(x): 0.9828945994377136 ,D(G(z)) 26.503205948503673\n",
      "epoch: 24 ,i: 300 ,Loss_D: 0.20991258323192596 ,Loss_G: 4.493983268737793 ,D(x): 0.8437825441360474 ,D(G(z)) 0.3571407940833049\n",
      "epoch: 24 ,i: 350 ,Loss_D: 0.09895505011081696 ,Loss_G: 5.741934776306152 ,D(x): 0.9333126544952393 ,D(G(z)) 1.8784351927958611\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 24 ,i: 400 ,Loss_D: 0.23851607739925385 ,Loss_G: 5.46933650970459 ,D(x): 0.9968855381011963 ,D(G(z)) 23.810241343502206\n",
      "epoch: 24 ,i: 450 ,Loss_D: 0.05119851976633072 ,Loss_G: 5.710647106170654 ,D(x): 0.9705981016159058 ,D(G(z)) 2.917310301624156\n",
      "epoch: 24 ,i: 500 ,Loss_D: 0.062193844467401505 ,Loss_G: 4.676537990570068 ,D(x): 0.9622902274131775 ,D(G(z)) 0.8759710818162169\n",
      "epoch: 24 ,i: 550 ,Loss_D: 0.042246099561452866 ,Loss_G: 5.519534111022949 ,D(x): 0.9814061522483826 ,D(G(z)) 2.1553037188919637\n",
      "epoch: 24 ,i: 600 ,Loss_D: 0.04192589595913887 ,Loss_G: 5.741110801696777 ,D(x): 0.9871635437011719 ,D(G(z)) 3.7953221936236887\n",
      "epoch: 24 ,i: 650 ,Loss_D: 0.1460285782814026 ,Loss_G: 6.966252326965332 ,D(x): 0.9984896183013916 ,D(G(z)) 51.18525807627251\n",
      "epoch: 24 ,i: 700 ,Loss_D: 0.3004049062728882 ,Loss_G: 3.79237961769104 ,D(x): 0.8493024706840515 ,D(G(z)) 1.3358332743992423\n",
      "epoch: 24 ,i: 750 ,Loss_D: 0.14019307494163513 ,Loss_G: 6.230342864990234 ,D(x): 0.9750046133995056 ,D(G(z)) 21.81129294454401\n",
      "epoch: 25 ,i: 0 ,Loss_D: 0.09967057406902313 ,Loss_G: 6.029618263244629 ,D(x): 0.9955416917800903 ,D(G(z)) 14.880356276238285\n",
      "epoch: 25 ,i: 50 ,Loss_D: 0.048283372074365616 ,Loss_G: 7.022067070007324 ,D(x): 0.9846829175949097 ,D(G(z)) 8.344041940737945\n",
      "epoch: 25 ,i: 100 ,Loss_D: 0.14059185981750488 ,Loss_G: 7.541204929351807 ,D(x): 0.9887794256210327 ,D(G(z)) 88.40307887629854\n",
      "epoch: 25 ,i: 150 ,Loss_D: 0.5456748604774475 ,Loss_G: 8.467660903930664 ,D(x): 0.9632626175880432 ,D(G(z)) 695.9410770971589\n",
      "epoch: 25 ,i: 200 ,Loss_D: 0.1309213936328888 ,Loss_G: 7.088447093963623 ,D(x): 0.9209388494491577 ,D(G(z)) 10.09810924172074\n",
      "epoch: 25 ,i: 250 ,Loss_D: 1.1699025630950928 ,Loss_G: 4.331281661987305 ,D(x): 0.5061294436454773 ,D(G(z)) 0.0037832072939390743\n",
      "epoch: 25 ,i: 300 ,Loss_D: 0.1838848888874054 ,Loss_G: 4.413299560546875 ,D(x): 0.9465583562850952 ,D(G(z)) 3.7205588736516413\n",
      "epoch: 25 ,i: 350 ,Loss_D: 0.07498036324977875 ,Loss_G: 5.116444110870361 ,D(x): 0.9715789556503296 ,D(G(z)) 3.0873536573458025\n",
      "epoch: 25 ,i: 400 ,Loss_D: 0.12751305103302002 ,Loss_G: 4.583805561065674 ,D(x): 0.9515737295150757 ,D(G(z)) 3.1158820866867813\n",
      "epoch: 25 ,i: 450 ,Loss_D: 0.10661022365093231 ,Loss_G: 5.406900405883789 ,D(x): 0.9906202554702759 ,D(G(z)) 9.004291561749618\n",
      "epoch: 25 ,i: 500 ,Loss_D: 0.031121449545025826 ,Loss_G: 4.243556022644043 ,D(x): 0.9857434630393982 ,D(G(z)) 0.4650226674985549\n",
      "epoch: 25 ,i: 550 ,Loss_D: 0.11876582354307175 ,Loss_G: 4.542331218719482 ,D(x): 0.955324649810791 ,D(G(z)) 3.2789728368595097\n",
      "epoch: 25 ,i: 600 ,Loss_D: 0.23912519216537476 ,Loss_G: 5.277883529663086 ,D(x): 0.9352360963821411 ,D(G(z)) 12.28005990574341\n",
      "epoch: 25 ,i: 650 ,Loss_D: 0.10041585564613342 ,Loss_G: 4.781245708465576 ,D(x): 0.9495052099227905 ,D(G(z)) 2.1292293443445374\n",
      "epoch: 25 ,i: 700 ,Loss_D: 0.1298917680978775 ,Loss_G: 5.472002029418945 ,D(x): 0.980365514755249 ,D(G(z)) 13.329066145140686\n",
      "epoch: 25 ,i: 750 ,Loss_D: 0.04768188297748566 ,Loss_G: 4.9163665771484375 ,D(x): 0.9818313717842102 ,D(G(z)) 1.8356071404827659\n",
      "epoch: 26 ,i: 0 ,Loss_D: 0.04601787030696869 ,Loss_G: 5.317340850830078 ,D(x): 0.9887619018554688 ,D(G(z)) 3.434916662600961\n",
      "epoch: 26 ,i: 50 ,Loss_D: 0.3544725775718689 ,Loss_G: 9.147618293762207 ,D(x): 0.9957098960876465 ,D(G(z)) 811.4875189377188\n",
      "epoch: 26 ,i: 100 ,Loss_D: 0.03127564862370491 ,Loss_G: 6.540871620178223 ,D(x): 0.9802135229110718 ,D(G(z)) 2.1668594139549913\n",
      "epoch: 26 ,i: 150 ,Loss_D: 0.06456203758716583 ,Loss_G: 6.080031394958496 ,D(x): 0.9827190637588501 ,D(G(z)) 7.142757070971493\n",
      "epoch: 26 ,i: 200 ,Loss_D: 0.04931555688381195 ,Loss_G: 6.2653045654296875 ,D(x): 0.979575514793396 ,D(G(z)) 4.9032374749324745\n",
      "epoch: 26 ,i: 250 ,Loss_D: 0.2803330421447754 ,Loss_G: 5.749931335449219 ,D(x): 0.8190501928329468 ,D(G(z)) 0.9298497809511566\n",
      "epoch: 26 ,i: 300 ,Loss_D: 0.10691903531551361 ,Loss_G: 5.380634784698486 ,D(x): 0.9604671597480774 ,D(G(z)) 5.628281412107262\n",
      "epoch: 26 ,i: 350 ,Loss_D: 0.18647684156894684 ,Loss_G: 8.942290306091309 ,D(x): 0.8554252982139587 ,D(G(z)) 1.4710766156038435\n",
      "epoch: 26 ,i: 400 ,Loss_D: 0.10890524089336395 ,Loss_G: 4.413660526275635 ,D(x): 0.9233226180076599 ,D(G(z)) 0.4663786224250799\n",
      "epoch: 26 ,i: 450 ,Loss_D: 0.033393025398254395 ,Loss_G: 4.9226250648498535 ,D(x): 0.9874598979949951 ,D(G(z)) 1.2840243640416968\n",
      "epoch: 26 ,i: 500 ,Loss_D: 0.8852792382240295 ,Loss_G: 1.622715711593628 ,D(x): 0.577215850353241 ,D(G(z)) 0.195374171083651\n",
      "epoch: 26 ,i: 550 ,Loss_D: 1.3244150876998901 ,Loss_G: 5.783807754516602 ,D(x): 0.9714718461036682 ,D(G(z)) 76.46483575329513\n",
      "epoch: 26 ,i: 600 ,Loss_D: 0.35878896713256836 ,Loss_G: 1.747645616531372 ,D(x): 0.783974289894104 ,D(G(z)) 0.1032597443156013\n",
      "epoch: 26 ,i: 650 ,Loss_D: 0.20079278945922852 ,Loss_G: 5.189194202423096 ,D(x): 0.8581246137619019 ,D(G(z)) 0.9198139799077127\n",
      "epoch: 26 ,i: 700 ,Loss_D: 0.3145628571510315 ,Loss_G: 3.066133499145508 ,D(x): 0.8259628415107727 ,D(G(z)) 0.5697771461287039\n",
      "epoch: 26 ,i: 750 ,Loss_D: 0.10501968860626221 ,Loss_G: 4.574286460876465 ,D(x): 0.9666428565979004 ,D(G(z)) 3.245192176942875\n",
      "epoch: 27 ,i: 0 ,Loss_D: 0.07894189655780792 ,Loss_G: 4.455295562744141 ,D(x): 0.9548749327659607 ,D(G(z)) 1.1386981993206131\n",
      "epoch: 27 ,i: 50 ,Loss_D: 0.04024890437722206 ,Loss_G: 4.1726460456848145 ,D(x): 0.9858920574188232 ,D(G(z)) 0.8904233350282914\n",
      "epoch: 27 ,i: 100 ,Loss_D: 0.06463689357042313 ,Loss_G: 4.841004371643066 ,D(x): 0.9856905937194824 ,D(G(z)) 2.4614670760142228\n",
      "epoch: 27 ,i: 150 ,Loss_D: 0.03426363319158554 ,Loss_G: 5.139310836791992 ,D(x): 0.9836132526397705 ,D(G(z)) 1.3295429002141181\n",
      "epoch: 27 ,i: 200 ,Loss_D: 0.03746175765991211 ,Loss_G: 7.013332366943359 ,D(x): 0.9821658134460449 ,D(G(z)) 5.856563419760911\n",
      "epoch: 27 ,i: 250 ,Loss_D: 0.05712508037686348 ,Loss_G: 4.489776611328125 ,D(x): 0.9628936052322388 ,D(G(z)) 0.7685140413498486\n",
      "epoch: 27 ,i: 300 ,Loss_D: 0.036541081964969635 ,Loss_G: 6.1183671951293945 ,D(x): 0.9948519468307495 ,D(G(z)) 6.0047316365740135\n",
      "epoch: 27 ,i: 350 ,Loss_D: 0.07945774495601654 ,Loss_G: 4.535386085510254 ,D(x): 0.9437116384506226 ,D(G(z)) 0.7757194692394488\n",
      "epoch: 27 ,i: 400 ,Loss_D: 0.20254382491111755 ,Loss_G: 7.124122142791748 ,D(x): 0.9819817543029785 ,D(G(z)) 93.79553019241875\n",
      "epoch: 27 ,i: 450 ,Loss_D: 0.745673656463623 ,Loss_G: 15.195840835571289 ,D(x): 0.9972468018531799 ,D(G(z)) 699130.1377247159\n",
      "epoch: 27 ,i: 500 ,Loss_D: 0.07542672753334045 ,Loss_G: 5.134713649749756 ,D(x): 0.9499915838241577 ,D(G(z)) 1.3626205247672538\n",
      "epoch: 27 ,i: 550 ,Loss_D: 0.05958256125450134 ,Loss_G: 5.446850776672363 ,D(x): 0.9668455123901367 ,D(G(z)) 1.8942141121948055\n",
      "epoch: 27 ,i: 600 ,Loss_D: 0.0800144374370575 ,Loss_G: 4.550657272338867 ,D(x): 0.9493415951728821 ,D(G(z)) 0.8094257855368033\n",
      "epoch: 27 ,i: 650 ,Loss_D: 0.10912512987852097 ,Loss_G: 4.3758440017700195 ,D(x): 0.9042718410491943 ,D(G(z)) 0.12026824756262731\n",
      "epoch: 27 ,i: 700 ,Loss_D: 0.10506264120340347 ,Loss_G: 3.848917245864868 ,D(x): 0.9146456718444824 ,D(G(z)) 0.19925597799527933\n",
      "epoch: 27 ,i: 750 ,Loss_D: 0.09949818253517151 ,Loss_G: 6.023167133331299 ,D(x): 0.9760727882385254 ,D(G(z)) 13.545516320121106\n",
      "epoch: 28 ,i: 0 ,Loss_D: 0.16765837371349335 ,Loss_G: 8.562043190002441 ,D(x): 0.9994642734527588 ,D(G(z)) 447.1127589010734\n",
      "epoch: 28 ,i: 50 ,Loss_D: 0.0655336007475853 ,Loss_G: 5.605035781860352 ,D(x): 0.9930885434150696 ,D(G(z)) 7.359599661017341\n",
      "epoch: 28 ,i: 100 ,Loss_D: 1.471785545349121 ,Loss_G: 0.471504807472229 ,D(x): 0.3336285352706909 ,D(G(z)) 3.3760778023434146e-05\n",
      "epoch: 28 ,i: 150 ,Loss_D: 0.13018867373466492 ,Loss_G: 3.975192070007324 ,D(x): 0.914681077003479 ,D(G(z)) 0.5113785540539211\n",
      "epoch: 28 ,i: 200 ,Loss_D: 0.11933425068855286 ,Loss_G: 5.581886291503906 ,D(x): 0.9546308517456055 ,D(G(z)) 4.526491507751558\n",
      "epoch: 28 ,i: 250 ,Loss_D: 0.12724687159061432 ,Loss_G: 6.734845161437988 ,D(x): 0.9732459187507629 ,D(G(z)) 24.310649832101614\n",
      "epoch: 28 ,i: 300 ,Loss_D: 0.28142648935317993 ,Loss_G: 2.8361384868621826 ,D(x): 0.8282262086868286 ,D(G(z)) 0.36380025636780283\n",
      "epoch: 28 ,i: 350 ,Loss_D: 0.1131797581911087 ,Loss_G: 5.690133094787598 ,D(x): 0.9820464849472046 ,D(G(z)) 11.591503032022946\n",
      "epoch: 28 ,i: 400 ,Loss_D: 0.08208450675010681 ,Loss_G: 6.890924453735352 ,D(x): 0.9983516931533813 ,D(G(z)) 36.15057494146309\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 28 ,i: 450 ,Loss_D: 0.0933590903878212 ,Loss_G: 4.45697021484375 ,D(x): 0.9583054184913635 ,D(G(z)) 1.8485855542174336\n",
      "epoch: 28 ,i: 500 ,Loss_D: 0.01855328306555748 ,Loss_G: 5.028514385223389 ,D(x): 0.993862509727478 ,D(G(z)) 0.9074874063552185\n",
      "epoch: 28 ,i: 550 ,Loss_D: 0.09064704924821854 ,Loss_G: 3.3078832626342773 ,D(x): 0.926274299621582 ,D(G(z)) 0.1510990781483886\n",
      "epoch: 28 ,i: 600 ,Loss_D: 0.025543708354234695 ,Loss_G: 5.678799629211426 ,D(x): 0.9865623712539673 ,D(G(z)) 1.414558755627249\n",
      "epoch: 28 ,i: 650 ,Loss_D: 0.13370448350906372 ,Loss_G: 4.384202480316162 ,D(x): 0.9224635362625122 ,D(G(z)) 1.2993198880508068\n",
      "epoch: 28 ,i: 700 ,Loss_D: 0.3819541335105896 ,Loss_G: 8.126895904541016 ,D(x): 0.9503705501556396 ,D(G(z)) 344.6033468396668\n",
      "epoch: 28 ,i: 750 ,Loss_D: 0.0637521892786026 ,Loss_G: 3.388770580291748 ,D(x): 0.992417573928833 ,D(G(z)) 0.6904894362839091\n",
      "epoch: 29 ,i: 0 ,Loss_D: 0.2443547397851944 ,Loss_G: 3.619034767150879 ,D(x): 0.8543782234191895 ,D(G(z)) 0.6825448111358421\n",
      "epoch: 29 ,i: 50 ,Loss_D: 0.11046945303678513 ,Loss_G: 4.482940673828125 ,D(x): 0.9387439489364624 ,D(G(z)) 1.172918613883844\n",
      "epoch: 29 ,i: 100 ,Loss_D: 0.023124095052480698 ,Loss_G: 6.429722785949707 ,D(x): 0.981998085975647 ,D(G(z)) 1.1931442124427134\n",
      "epoch: 29 ,i: 150 ,Loss_D: 0.31832537055015564 ,Loss_G: 8.728578567504883 ,D(x): 0.9957399368286133 ,D(G(z)) 651.3869387605185\n",
      "epoch: 29 ,i: 200 ,Loss_D: 0.12071292102336884 ,Loss_G: 4.111578464508057 ,D(x): 0.9315056800842285 ,D(G(z)) 1.2189367945910308\n",
      "epoch: 29 ,i: 250 ,Loss_D: 0.05788068473339081 ,Loss_G: 4.6899261474609375 ,D(x): 0.9599734544754028 ,D(G(z)) 0.5320709397648805\n",
      "epoch: 29 ,i: 300 ,Loss_D: 0.06858672946691513 ,Loss_G: 6.1846113204956055 ,D(x): 0.9970049858093262 ,D(G(z)) 16.789949449749642\n",
      "epoch: 29 ,i: 350 ,Loss_D: 0.03172038123011589 ,Loss_G: 5.217895030975342 ,D(x): 0.9934598803520203 ,D(G(z)) 2.139895555077895\n",
      "epoch: 29 ,i: 400 ,Loss_D: 0.05563762038946152 ,Loss_G: 6.444239139556885 ,D(x): 0.9562828540802002 ,D(G(z)) 1.3720750251289056\n",
      "epoch: 29 ,i: 450 ,Loss_D: 0.06431008130311966 ,Loss_G: 6.280029773712158 ,D(x): 0.94697105884552 ,D(G(z)) 0.9273259088909585\n",
      "epoch: 29 ,i: 500 ,Loss_D: 0.827709436416626 ,Loss_G: 10.100932121276855 ,D(x): 0.9930027723312378 ,D(G(z)) 2666.8047085254266\n",
      "epoch: 29 ,i: 550 ,Loss_D: 0.04511759430170059 ,Loss_G: 6.715996742248535 ,D(x): 0.9690648317337036 ,D(G(z)) 1.923188937332428\n",
      "epoch: 29 ,i: 600 ,Loss_D: 0.435479998588562 ,Loss_G: 4.465542793273926 ,D(x): 0.716705322265625 ,D(G(z)) 0.346982272539127\n",
      "epoch: 29 ,i: 650 ,Loss_D: 0.15474823117256165 ,Loss_G: 5.74687385559082 ,D(x): 0.9074288606643677 ,D(G(z)) 2.6191642572123572\n",
      "epoch: 29 ,i: 700 ,Loss_D: 0.12022008001804352 ,Loss_G: 5.112746238708496 ,D(x): 0.9359384775161743 ,D(G(z)) 2.523061319591759\n",
      "epoch: 29 ,i: 750 ,Loss_D: 0.1430467963218689 ,Loss_G: 4.235069274902344 ,D(x): 0.9234974980354309 ,D(G(z)) 1.9430572386736633\n",
      "epoch: 30 ,i: 0 ,Loss_D: 0.08697956800460815 ,Loss_G: 4.605907917022705 ,D(x): 0.9918866157531738 ,D(G(z)) 3.8631074339865057\n",
      "epoch: 30 ,i: 50 ,Loss_D: 0.13927847146987915 ,Loss_G: 6.536276817321777 ,D(x): 0.9954022765159607 ,D(G(z)) 35.48561685874227\n",
      "epoch: 30 ,i: 100 ,Loss_D: 0.09310853481292725 ,Loss_G: 5.727661609649658 ,D(x): 0.9924124479293823 ,D(G(z)) 13.116133444867444\n",
      "epoch: 30 ,i: 150 ,Loss_D: 0.11280949413776398 ,Loss_G: 6.295351505279541 ,D(x): 0.984471321105957 ,D(G(z)) 24.648149434603628\n",
      "epoch: 30 ,i: 200 ,Loss_D: 0.09929479658603668 ,Loss_G: 4.012821197509766 ,D(x): 0.9343905448913574 ,D(G(z)) 0.5133440562712879\n",
      "epoch: 30 ,i: 250 ,Loss_D: 0.12694714963436127 ,Loss_G: 5.205197334289551 ,D(x): 0.902728796005249 ,D(G(z)) 0.7253183102543914\n",
      "epoch: 30 ,i: 300 ,Loss_D: 0.14394241571426392 ,Loss_G: 7.317615509033203 ,D(x): 0.9886150360107422 ,D(G(z)) 59.369410814409534\n",
      "epoch: 30 ,i: 350 ,Loss_D: 0.10292750597000122 ,Loss_G: 5.294951438903809 ,D(x): 0.9620144963264465 ,D(G(z)) 4.367743363479381\n",
      "epoch: 30 ,i: 400 ,Loss_D: 0.09509860724210739 ,Loss_G: 6.932402610778809 ,D(x): 0.9937424659729004 ,D(G(z)) 29.877944275308778\n",
      "epoch: 30 ,i: 450 ,Loss_D: 0.1533043384552002 ,Loss_G: 2.6924777030944824 ,D(x): 0.8856335878372192 ,D(G(z)) 0.08020243372302747\n",
      "epoch: 30 ,i: 500 ,Loss_D: 0.2812049984931946 ,Loss_G: 2.989957332611084 ,D(x): 0.8640952110290527 ,D(G(z)) 0.6224872845240489\n",
      "epoch: 30 ,i: 550 ,Loss_D: 0.08172683417797089 ,Loss_G: 5.969476699829102 ,D(x): 0.9822463989257812 ,D(G(z)) 8.552884316351335\n",
      "epoch: 30 ,i: 600 ,Loss_D: 0.084569051861763 ,Loss_G: 5.2731218338012695 ,D(x): 0.9587164521217346 ,D(G(z)) 2.156513191352129\n",
      "epoch: 30 ,i: 650 ,Loss_D: 0.09436731040477753 ,Loss_G: 4.735648155212402 ,D(x): 0.9324381351470947 ,D(G(z)) 1.0272335727612207\n",
      "epoch: 30 ,i: 700 ,Loss_D: 0.09560905396938324 ,Loss_G: 7.086664199829102 ,D(x): 0.975297749042511 ,D(G(z)) 28.909046291736267\n",
      "epoch: 30 ,i: 750 ,Loss_D: 0.04370414465665817 ,Loss_G: 5.1626691818237305 ,D(x): 0.983381986618042 ,D(G(z)) 1.6600646644624089\n",
      "epoch: 31 ,i: 0 ,Loss_D: 0.07424329966306686 ,Loss_G: 6.259527206420898 ,D(x): 0.993060827255249 ,D(G(z)) 9.933872879038221\n",
      "epoch: 31 ,i: 50 ,Loss_D: 0.038978029042482376 ,Loss_G: 5.0666399002075195 ,D(x): 0.9851763248443604 ,D(G(z)) 1.4447217705191584\n",
      "epoch: 31 ,i: 100 ,Loss_D: 0.15602131187915802 ,Loss_G: 6.731377124786377 ,D(x): 0.9843524694442749 ,D(G(z)) 50.77758080006167\n",
      "epoch: 31 ,i: 150 ,Loss_D: 0.03521125763654709 ,Loss_G: 5.658941268920898 ,D(x): 0.9947350025177002 ,D(G(z)) 4.229781386092886\n",
      "epoch: 31 ,i: 200 ,Loss_D: 0.021773429587483406 ,Loss_G: 6.047587871551514 ,D(x): 0.9978652000427246 ,D(G(z)) 2.775669659674595\n",
      "epoch: 31 ,i: 250 ,Loss_D: 0.21578435599803925 ,Loss_G: 7.55001163482666 ,D(x): 0.8448079228401184 ,D(G(z)) 4.324219365068233\n",
      "epoch: 31 ,i: 300 ,Loss_D: 0.0572553351521492 ,Loss_G: 5.513618469238281 ,D(x): 0.9871708154678345 ,D(G(z)) 4.481774787917745\n",
      "epoch: 31 ,i: 350 ,Loss_D: 0.04121878743171692 ,Loss_G: 6.216198921203613 ,D(x): 0.9877421855926514 ,D(G(z)) 4.894293580588207\n",
      "epoch: 31 ,i: 400 ,Loss_D: 0.20037098228931427 ,Loss_G: 6.838968276977539 ,D(x): 0.9630216360092163 ,D(G(z)) 42.44449167970375\n",
      "epoch: 31 ,i: 450 ,Loss_D: 0.049149107187986374 ,Loss_G: 3.860431671142578 ,D(x): 0.9945182204246521 ,D(G(z)) 0.8254495983847056\n",
      "epoch: 31 ,i: 500 ,Loss_D: 0.3163966238498688 ,Loss_G: 3.468698024749756 ,D(x): 0.77801513671875 ,D(G(z)) 0.15112846450592343\n",
      "epoch: 31 ,i: 550 ,Loss_D: 0.11543621867895126 ,Loss_G: 5.707706928253174 ,D(x): 0.9918056726455688 ,D(G(z)) 13.332241044759849\n",
      "epoch: 31 ,i: 600 ,Loss_D: 0.05460750684142113 ,Loss_G: 5.534976482391357 ,D(x): 0.9729392528533936 ,D(G(z)) 2.2100400423213933\n",
      "epoch: 31 ,i: 650 ,Loss_D: 0.09840751439332962 ,Loss_G: 4.9943647384643555 ,D(x): 0.9593746662139893 ,D(G(z)) 2.7797688313251476\n",
      "epoch: 31 ,i: 700 ,Loss_D: 0.06481774896383286 ,Loss_G: 5.491660118103027 ,D(x): 0.9739007949829102 ,D(G(z)) 3.363902768366019\n",
      "epoch: 31 ,i: 750 ,Loss_D: 0.032639630138874054 ,Loss_G: 5.398917198181152 ,D(x): 0.9903870820999146 ,D(G(z)) 2.51521387531413\n",
      "epoch: 32 ,i: 0 ,Loss_D: 0.5118562579154968 ,Loss_G: 10.375468254089355 ,D(x): 0.9996298551559448 ,D(G(z)) 4957.959300132581\n",
      "epoch: 32 ,i: 50 ,Loss_D: 0.05662830173969269 ,Loss_G: 5.113194942474365 ,D(x): 0.9848411083221436 ,D(G(z)) 3.183844764421147\n",
      "epoch: 32 ,i: 100 ,Loss_D: 0.05102938041090965 ,Loss_G: 6.322396278381348 ,D(x): 0.9961230754852295 ,D(G(z)) 9.767153006808313\n",
      "epoch: 32 ,i: 150 ,Loss_D: 0.04783923923969269 ,Loss_G: 5.8348846435546875 ,D(x): 0.9721931219100952 ,D(G(z)) 2.304416958276171\n",
      "epoch: 32 ,i: 200 ,Loss_D: 0.022071219980716705 ,Loss_G: 6.213868141174316 ,D(x): 0.9857031106948853 ,D(G(z)) 0.9004805450814983\n",
      "epoch: 32 ,i: 250 ,Loss_D: 0.4345259368419647 ,Loss_G: 4.464098930358887 ,D(x): 0.7431793212890625 ,D(G(z)) 0.02850013178347515\n",
      "epoch: 32 ,i: 300 ,Loss_D: 0.05945467948913574 ,Loss_G: 6.171543121337891 ,D(x): 0.9692696928977966 ,D(G(z)) 3.8632350686898107\n",
      "epoch: 32 ,i: 350 ,Loss_D: 0.024956941604614258 ,Loss_G: 5.950303077697754 ,D(x): 0.985109806060791 ,D(G(z)) 1.1841384548222929\n",
      "epoch: 32 ,i: 400 ,Loss_D: 0.27490270137786865 ,Loss_G: 11.345327377319336 ,D(x): 0.9977160692214966 ,D(G(z)) 6306.220010133176\n",
      "epoch: 32 ,i: 450 ,Loss_D: 0.5779174566268921 ,Loss_G: 13.743124961853027 ,D(x): 0.9999285936355591 ,D(G(z)) 154872.47291560375\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 32 ,i: 500 ,Loss_D: 0.06662546098232269 ,Loss_G: 7.311117172241211 ,D(x): 0.9944351315498352 ,D(G(z)) 32.39801422310001\n",
      "epoch: 32 ,i: 550 ,Loss_D: 0.25535380840301514 ,Loss_G: 8.400680541992188 ,D(x): 0.9986204504966736 ,D(G(z)) 409.58582652650625\n",
      "epoch: 32 ,i: 600 ,Loss_D: 0.023621540516614914 ,Loss_G: 6.816941261291504 ,D(x): 0.984990119934082 ,D(G(z)) 1.869670315276743\n",
      "epoch: 32 ,i: 650 ,Loss_D: 0.01659473404288292 ,Loss_G: 6.046743392944336 ,D(x): 0.9920600652694702 ,D(G(z)) 1.5024844752646982\n",
      "epoch: 32 ,i: 700 ,Loss_D: 0.2204866111278534 ,Loss_G: 7.854714393615723 ,D(x): 0.8551727533340454 ,D(G(z)) 1.5405970488574636\n",
      "epoch: 32 ,i: 750 ,Loss_D: 0.04716549813747406 ,Loss_G: 5.683899879455566 ,D(x): 0.9767208099365234 ,D(G(z)) 1.7474001865943543\n",
      "epoch: 33 ,i: 0 ,Loss_D: 0.06201944127678871 ,Loss_G: 4.530036449432373 ,D(x): 0.9642963409423828 ,D(G(z)) 0.8142994885504125\n",
      "epoch: 33 ,i: 50 ,Loss_D: 0.03559783846139908 ,Loss_G: 5.808353424072266 ,D(x): 0.979751467704773 ,D(G(z)) 2.3551006778889407\n",
      "epoch: 33 ,i: 100 ,Loss_D: 0.21748848259449005 ,Loss_G: 5.893470764160156 ,D(x): 0.8285204768180847 ,D(G(z)) 0.12483954574338071\n",
      "epoch: 33 ,i: 150 ,Loss_D: 0.08895842730998993 ,Loss_G: 6.402099609375 ,D(x): 0.9767528772354126 ,D(G(z)) 13.385756328562495\n",
      "epoch: 33 ,i: 200 ,Loss_D: 0.05838058143854141 ,Loss_G: 5.557778358459473 ,D(x): 0.9740225076675415 ,D(G(z)) 2.8695907111490886\n",
      "epoch: 33 ,i: 250 ,Loss_D: 0.03662166744470596 ,Loss_G: 5.204465866088867 ,D(x): 0.9703400135040283 ,D(G(z)) 0.41450449607114087\n",
      "epoch: 33 ,i: 300 ,Loss_D: 0.08740539103746414 ,Loss_G: 3.357512950897217 ,D(x): 0.9323682188987732 ,D(G(z)) 0.17280135180841133\n",
      "epoch: 33 ,i: 350 ,Loss_D: 0.11295638978481293 ,Loss_G: 7.371908664703369 ,D(x): 0.9970894455909729 ,D(G(z)) 70.32106360171292\n",
      "epoch: 33 ,i: 400 ,Loss_D: 6.80385160446167 ,Loss_G: 0.0009933044202625751 ,D(x): 0.006702966522425413 ,D(G(z)) 0.0001350028709426447\n",
      "epoch: 33 ,i: 450 ,Loss_D: 2.481830358505249 ,Loss_G: 1.09726083278656 ,D(x): 0.22186730802059174 ,D(G(z)) 0.0006679096846952355\n",
      "epoch: 33 ,i: 500 ,Loss_D: 0.4280130863189697 ,Loss_G: 8.695196151733398 ,D(x): 0.9661872386932373 ,D(G(z)) 627.2434214028008\n",
      "epoch: 33 ,i: 550 ,Loss_D: 0.17781907320022583 ,Loss_G: 5.939986228942871 ,D(x): 0.9472191333770752 ,D(G(z)) 19.33581990793282\n",
      "epoch: 33 ,i: 600 ,Loss_D: 0.8454233407974243 ,Loss_G: 4.793835639953613 ,D(x): 0.978906512260437 ,D(G(z)) 14.576521648769678\n",
      "epoch: 33 ,i: 650 ,Loss_D: 0.1023891419172287 ,Loss_G: 6.060609340667725 ,D(x): 0.9667701721191406 ,D(G(z)) 9.045529144225164\n",
      "epoch: 33 ,i: 700 ,Loss_D: 1.6987292766571045 ,Loss_G: 1.9980182647705078 ,D(x): 0.29358214139938354 ,D(G(z)) 0.0020157587674761663\n",
      "epoch: 33 ,i: 750 ,Loss_D: 0.10264577716588974 ,Loss_G: 4.571353435516357 ,D(x): 0.9769635200500488 ,D(G(z)) 3.671067189295053\n",
      "epoch: 34 ,i: 0 ,Loss_D: 4.004315376281738 ,Loss_G: 12.727804183959961 ,D(x): 0.9999850392341614 ,D(G(z)) 62196.54513415976\n",
      "epoch: 34 ,i: 50 ,Loss_D: 0.2043258398771286 ,Loss_G: 3.5455877780914307 ,D(x): 0.8445582389831543 ,D(G(z)) 0.16292706567110196\n",
      "epoch: 34 ,i: 100 ,Loss_D: 0.06905855983495712 ,Loss_G: 4.714211463928223 ,D(x): 0.9457271099090576 ,D(G(z)) 0.4354988157100425\n",
      "epoch: 34 ,i: 150 ,Loss_D: 0.5350839495658875 ,Loss_G: 3.652060031890869 ,D(x): 0.6551203727722168 ,D(G(z)) 0.013545138088850654\n",
      "epoch: 34 ,i: 200 ,Loss_D: 0.10215805470943451 ,Loss_G: 6.142677307128906 ,D(x): 0.9132876992225647 ,D(G(z)) 0.6998541940239338\n",
      "epoch: 34 ,i: 250 ,Loss_D: 0.06801387667655945 ,Loss_G: 4.439304351806641 ,D(x): 0.9618706107139587 ,D(G(z)) 1.1540873441766049\n",
      "epoch: 34 ,i: 300 ,Loss_D: 0.11779304593801498 ,Loss_G: 4.018099784851074 ,D(x): 0.9180217981338501 ,D(G(z)) 0.5516323127789095\n",
      "epoch: 34 ,i: 350 ,Loss_D: 0.18804916739463806 ,Loss_G: 6.374627590179443 ,D(x): 0.9984428882598877 ,D(G(z)) 54.18200198498898\n",
      "epoch: 34 ,i: 400 ,Loss_D: 0.04286118969321251 ,Loss_G: 6.302945137023926 ,D(x): 0.9924437999725342 ,D(G(z)) 6.288415001801834\n",
      "epoch: 34 ,i: 450 ,Loss_D: 0.05815303325653076 ,Loss_G: 4.972058296203613 ,D(x): 0.9674420356750488 ,D(G(z)) 1.3455353072697258\n",
      "epoch: 34 ,i: 500 ,Loss_D: 0.10344745963811874 ,Loss_G: 6.184976577758789 ,D(x): 0.9991504549980164 ,D(G(z)) 23.7524773770598\n",
      "epoch: 34 ,i: 550 ,Loss_D: 1.0121490955352783 ,Loss_G: 11.630586624145508 ,D(x): 0.9993486404418945 ,D(G(z)) 12714.077750101802\n",
      "epoch: 34 ,i: 600 ,Loss_D: 0.09886854887008667 ,Loss_G: 3.709388494491577 ,D(x): 0.9703758358955383 ,D(G(z)) 1.3839279452968913\n",
      "epoch: 34 ,i: 650 ,Loss_D: 0.07015812397003174 ,Loss_G: 6.097772598266602 ,D(x): 0.9887484312057495 ,D(G(z)) 5.367784035872849\n",
      "epoch: 34 ,i: 700 ,Loss_D: 0.16132855415344238 ,Loss_G: 3.010319232940674 ,D(x): 0.8742823004722595 ,D(G(z)) 0.13795537186230672\n",
      "epoch: 34 ,i: 750 ,Loss_D: 0.03208377957344055 ,Loss_G: 5.800979137420654 ,D(x): 0.9793697595596313 ,D(G(z)) 1.4142333018807907\n",
      "epoch: 35 ,i: 0 ,Loss_D: 0.4860752522945404 ,Loss_G: 13.325066566467285 ,D(x): 0.9999015927314758 ,D(G(z)) 61751.70905762246\n",
      "epoch: 35 ,i: 50 ,Loss_D: 0.12991869449615479 ,Loss_G: 5.7567291259765625 ,D(x): 0.9426303505897522 ,D(G(z)) 5.590261101989446\n",
      "epoch: 35 ,i: 100 ,Loss_D: 0.07331731170415878 ,Loss_G: 5.826298236846924 ,D(x): 0.98734050989151 ,D(G(z)) 6.41481279051613\n",
      "epoch: 35 ,i: 150 ,Loss_D: 0.05140361562371254 ,Loss_G: 5.675781726837158 ,D(x): 0.9595762491226196 ,D(G(z)) 0.8505530882555901\n",
      "epoch: 35 ,i: 200 ,Loss_D: 0.07549408078193665 ,Loss_G: 6.160665512084961 ,D(x): 0.9366069436073303 ,D(G(z)) 0.3896871999280686\n",
      "epoch: 35 ,i: 250 ,Loss_D: 0.08302384614944458 ,Loss_G: 4.46505069732666 ,D(x): 0.9585587978363037 ,D(G(z)) 0.9924483941657136\n",
      "epoch: 35 ,i: 300 ,Loss_D: 0.1632883995771408 ,Loss_G: 5.8007307052612305 ,D(x): 0.8715870380401611 ,D(G(z)) 0.5028656983158998\n",
      "epoch: 35 ,i: 350 ,Loss_D: 0.22228354215621948 ,Loss_G: 3.497885227203369 ,D(x): 0.8479354977607727 ,D(G(z)) 0.050625563780973125\n",
      "epoch: 35 ,i: 400 ,Loss_D: 0.027922986075282097 ,Loss_G: 6.358791351318359 ,D(x): 0.9845510721206665 ,D(G(z)) 2.3696885665631884\n",
      "epoch: 35 ,i: 450 ,Loss_D: 0.134800523519516 ,Loss_G: 7.741490364074707 ,D(x): 0.9886130094528198 ,D(G(z)) 90.73066594617809\n",
      "epoch: 35 ,i: 500 ,Loss_D: 1.0954174995422363 ,Loss_G: 4.024590492248535 ,D(x): 0.4773331582546234 ,D(G(z)) 0.0019884923087099787\n",
      "epoch: 35 ,i: 550 ,Loss_D: 0.19681039452552795 ,Loss_G: 4.8730788230896 ,D(x): 0.9336745738983154 ,D(G(z)) 5.397280613616483\n",
      "epoch: 35 ,i: 600 ,Loss_D: 0.3136301040649414 ,Loss_G: 7.978442192077637 ,D(x): 0.9915478229522705 ,D(G(z)) 189.91315685927853\n",
      "epoch: 35 ,i: 650 ,Loss_D: 0.09220583736896515 ,Loss_G: 4.192440032958984 ,D(x): 0.9391677975654602 ,D(G(z)) 0.5601453587656071\n",
      "epoch: 35 ,i: 700 ,Loss_D: 0.046770643442869186 ,Loss_G: 5.408984661102295 ,D(x): 0.9920728802680969 ,D(G(z)) 3.8693448288823693\n",
      "epoch: 35 ,i: 750 ,Loss_D: 0.0914331004023552 ,Loss_G: 8.147881507873535 ,D(x): 0.9976083040237427 ,D(G(z)) 110.0262397775355\n",
      "epoch: 36 ,i: 0 ,Loss_D: 0.5371554493904114 ,Loss_G: 11.24986457824707 ,D(x): 0.9964026212692261 ,D(G(z)) 14775.975344516528\n",
      "epoch: 36 ,i: 50 ,Loss_D: 0.07855492830276489 ,Loss_G: 7.413572311401367 ,D(x): 0.9975810050964355 ,D(G(z)) 31.13937682884838\n",
      "epoch: 36 ,i: 100 ,Loss_D: 0.024779103696346283 ,Loss_G: 6.8211565017700195 ,D(x): 0.9916303753852844 ,D(G(z)) 3.2016741616898736\n",
      "epoch: 36 ,i: 150 ,Loss_D: 0.06237739697098732 ,Loss_G: 4.329675674438477 ,D(x): 0.9498392343521118 ,D(G(z)) 0.21674984229714928\n",
      "epoch: 36 ,i: 200 ,Loss_D: 0.02944001369178295 ,Loss_G: 6.143256187438965 ,D(x): 0.9910541772842407 ,D(G(z)) 3.2760256740662057\n",
      "epoch: 36 ,i: 250 ,Loss_D: 0.04626812785863876 ,Loss_G: 5.732390403747559 ,D(x): 0.9833371639251709 ,D(G(z)) 3.4940426062799346\n",
      "epoch: 36 ,i: 300 ,Loss_D: 0.06637346744537354 ,Loss_G: 6.77901554107666 ,D(x): 0.9935638904571533 ,D(G(z)) 18.145156740920775\n",
      "epoch: 36 ,i: 350 ,Loss_D: 0.1857958436012268 ,Loss_G: 5.841035842895508 ,D(x): 0.9966311454772949 ,D(G(z)) 20.89835210690672\n",
      "epoch: 36 ,i: 400 ,Loss_D: 0.07621626555919647 ,Loss_G: 4.85958194732666 ,D(x): 0.9463455080986023 ,D(G(z)) 0.6039087066507207\n",
      "epoch: 36 ,i: 450 ,Loss_D: 0.021802525967359543 ,Loss_G: 6.961479187011719 ,D(x): 0.9898461103439331 ,D(G(z)) 2.5833378153185946\n",
      "epoch: 36 ,i: 500 ,Loss_D: 0.5994141697883606 ,Loss_G: 4.145333290100098 ,D(x): 0.9848654270172119 ,D(G(z)) 10.460832648917346\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 36 ,i: 550 ,Loss_D: 0.23329128324985504 ,Loss_G: 3.994424819946289 ,D(x): 0.8777002096176147 ,D(G(z)) 1.0766510986778883\n",
      "epoch: 36 ,i: 600 ,Loss_D: 0.22515270113945007 ,Loss_G: 2.8005990982055664 ,D(x): 0.9456521272659302 ,D(G(z)) 1.0589734547438834\n",
      "epoch: 36 ,i: 650 ,Loss_D: 0.0867604911327362 ,Loss_G: 6.649098873138428 ,D(x): 0.9365096092224121 ,D(G(z)) 2.6338835705696066\n",
      "epoch: 36 ,i: 700 ,Loss_D: 0.12389274686574936 ,Loss_G: 6.587428092956543 ,D(x): 0.9578631520271301 ,D(G(z)) 10.310791981866815\n",
      "epoch: 36 ,i: 750 ,Loss_D: 0.0622885599732399 ,Loss_G: 6.638804912567139 ,D(x): 0.9936049580574036 ,D(G(z)) 16.04201284617282\n",
      "epoch: 37 ,i: 0 ,Loss_D: 0.1263670027256012 ,Loss_G: 7.887664794921875 ,D(x): 0.9972923398017883 ,D(G(z)) 165.5184976445222\n",
      "epoch: 37 ,i: 50 ,Loss_D: 0.2991260290145874 ,Loss_G: 2.224196434020996 ,D(x): 0.7900669574737549 ,D(G(z)) 0.022501168393204107\n",
      "epoch: 37 ,i: 100 ,Loss_D: 0.04539145529270172 ,Loss_G: 6.204169273376465 ,D(x): 0.9900018572807312 ,D(G(z)) 6.599508931990085\n",
      "epoch: 37 ,i: 150 ,Loss_D: 0.03948803246021271 ,Loss_G: 6.534224510192871 ,D(x): 0.995423436164856 ,D(G(z)) 8.162147264213425\n",
      "epoch: 37 ,i: 200 ,Loss_D: 0.07877741754055023 ,Loss_G: 4.934957027435303 ,D(x): 0.9610125422477722 ,D(G(z)) 1.9842628348770688\n",
      "epoch: 37 ,i: 250 ,Loss_D: 0.07091451436281204 ,Loss_G: 5.691866874694824 ,D(x): 0.9586992263793945 ,D(G(z)) 3.0200655665960245\n",
      "epoch: 37 ,i: 300 ,Loss_D: 0.08362753689289093 ,Loss_G: 6.101619720458984 ,D(x): 0.9479724168777466 ,D(G(z)) 3.3249669465650133\n",
      "epoch: 37 ,i: 350 ,Loss_D: 0.4290092885494232 ,Loss_G: 6.459532737731934 ,D(x): 0.9817239046096802 ,D(G(z)) 67.81130827382965\n",
      "epoch: 37 ,i: 400 ,Loss_D: 0.5328311324119568 ,Loss_G: 2.0415267944335938 ,D(x): 0.7239227890968323 ,D(G(z)) 0.450040102003596\n",
      "epoch: 37 ,i: 450 ,Loss_D: 0.1160169392824173 ,Loss_G: 7.499159336090088 ,D(x): 0.9451596736907959 ,D(G(z)) 14.866746095800774\n",
      "epoch: 37 ,i: 500 ,Loss_D: 0.04672982916235924 ,Loss_G: 6.551401615142822 ,D(x): 0.96894371509552 ,D(G(z)) 2.0461215420705794\n",
      "epoch: 37 ,i: 550 ,Loss_D: 0.02190525457262993 ,Loss_G: 6.3399763107299805 ,D(x): 0.9915038347244263 ,D(G(z)) 3.13177390141114\n",
      "epoch: 37 ,i: 600 ,Loss_D: 0.06582392007112503 ,Loss_G: 5.782618045806885 ,D(x): 0.951417863368988 ,D(G(z)) 1.383016192180075\n",
      "epoch: 37 ,i: 650 ,Loss_D: 0.1096692830324173 ,Loss_G: 4.374814033508301 ,D(x): 0.9224872589111328 ,D(G(z)) 0.12852544580698294\n",
      "epoch: 37 ,i: 700 ,Loss_D: 0.07115346193313599 ,Loss_G: 5.6672587394714355 ,D(x): 0.9790056943893433 ,D(G(z)) 6.487580948882544\n",
      "epoch: 37 ,i: 750 ,Loss_D: 0.03514506667852402 ,Loss_G: 5.3928985595703125 ,D(x): 0.9859142899513245 ,D(G(z)) 1.9336306351037575\n",
      "epoch: 38 ,i: 0 ,Loss_D: 0.06342917680740356 ,Loss_G: 6.5375776290893555 ,D(x): 0.9963902831077576 ,D(G(z)) 18.508438782635352\n",
      "epoch: 38 ,i: 50 ,Loss_D: 0.10807444900274277 ,Loss_G: 6.6574530601501465 ,D(x): 0.9929471611976624 ,D(G(z)) 36.11961658776049\n",
      "epoch: 38 ,i: 100 ,Loss_D: 0.0372094064950943 ,Loss_G: 6.528685569763184 ,D(x): 0.9818457961082458 ,D(G(z)) 3.1997737609201633\n",
      "epoch: 38 ,i: 150 ,Loss_D: 0.11831411719322205 ,Loss_G: 3.9966232776641846 ,D(x): 0.9291245937347412 ,D(G(z)) 0.6367097408609239\n",
      "epoch: 38 ,i: 200 ,Loss_D: 0.0558692067861557 ,Loss_G: 5.5268449783325195 ,D(x): 0.9968637824058533 ,D(G(z)) 5.50562732329674\n",
      "epoch: 38 ,i: 250 ,Loss_D: 0.04421505331993103 ,Loss_G: 5.859719276428223 ,D(x): 0.9931219220161438 ,D(G(z)) 5.853890696962943\n",
      "epoch: 38 ,i: 300 ,Loss_D: 0.08048676699399948 ,Loss_G: 7.0482330322265625 ,D(x): 0.9886134266853333 ,D(G(z)) 30.346602029351534\n",
      "epoch: 38 ,i: 350 ,Loss_D: 0.020990295335650444 ,Loss_G: 6.030361175537109 ,D(x): 0.9863086938858032 ,D(G(z)) 1.073249852733258\n",
      "epoch: 38 ,i: 400 ,Loss_D: 0.2691184878349304 ,Loss_G: 3.5633633136749268 ,D(x): 0.8414810299873352 ,D(G(z)) 0.3968003414947216\n",
      "epoch: 38 ,i: 450 ,Loss_D: 0.07708277553319931 ,Loss_G: 7.384833335876465 ,D(x): 0.9864708185195923 ,D(G(z)) 21.44966107195418\n",
      "epoch: 38 ,i: 500 ,Loss_D: 0.158619225025177 ,Loss_G: 5.135390281677246 ,D(x): 0.9665365815162659 ,D(G(z)) 3.9769058371415302\n",
      "epoch: 38 ,i: 550 ,Loss_D: 0.13392671942710876 ,Loss_G: 5.493141174316406 ,D(x): 0.907963752746582 ,D(G(z)) 1.3633278185226538\n",
      "epoch: 38 ,i: 600 ,Loss_D: 0.13692641258239746 ,Loss_G: 4.686086654663086 ,D(x): 0.9041662216186523 ,D(G(z)) 0.3774148636683147\n",
      "epoch: 38 ,i: 650 ,Loss_D: 0.03310815244913101 ,Loss_G: 6.225747585296631 ,D(x): 0.9937232136726379 ,D(G(z)) 3.0755441137842\n",
      "epoch: 38 ,i: 700 ,Loss_D: 0.088253453373909 ,Loss_G: 5.139524459838867 ,D(x): 0.946609377861023 ,D(G(z)) 1.3668843154398345\n",
      "epoch: 38 ,i: 750 ,Loss_D: 0.07848025858402252 ,Loss_G: 5.825888633728027 ,D(x): 0.983227014541626 ,D(G(z)) 5.13068601707574\n",
      "epoch: 39 ,i: 0 ,Loss_D: 0.0489766001701355 ,Loss_G: 5.654801845550537 ,D(x): 0.9920070171356201 ,D(G(z)) 4.902835385737283\n",
      "epoch: 39 ,i: 50 ,Loss_D: 0.3188694715499878 ,Loss_G: 3.137223720550537 ,D(x): 0.8384357690811157 ,D(G(z)) 0.40809407356133703\n",
      "epoch: 39 ,i: 100 ,Loss_D: 0.21431516110897064 ,Loss_G: 4.611246109008789 ,D(x): 0.8350133299827576 ,D(G(z)) 0.08191138186038381\n",
      "epoch: 39 ,i: 150 ,Loss_D: 0.38182663917541504 ,Loss_G: 9.589184761047363 ,D(x): 0.999390721321106 ,D(G(z)) 1372.751850361569\n",
      "epoch: 39 ,i: 200 ,Loss_D: 0.05230923742055893 ,Loss_G: 5.629782199859619 ,D(x): 0.9619665145874023 ,D(G(z)) 0.9484460802431958\n",
      "epoch: 39 ,i: 250 ,Loss_D: 0.02140655554831028 ,Loss_G: 6.270037651062012 ,D(x): 0.9852818846702576 ,D(G(z)) 1.0862761406882095\n",
      "epoch: 39 ,i: 300 ,Loss_D: 0.03661566972732544 ,Loss_G: 6.234724044799805 ,D(x): 0.9815894365310669 ,D(G(z)) 2.9821401430004495\n",
      "epoch: 39 ,i: 350 ,Loss_D: 0.04208454117178917 ,Loss_G: 5.0919108390808105 ,D(x): 0.9762042164802551 ,D(G(z)) 1.1111535533082157\n",
      "epoch: 39 ,i: 400 ,Loss_D: 0.2560715973377228 ,Loss_G: 4.941527366638184 ,D(x): 0.9779678583145142 ,D(G(z)) 12.49840103087253\n",
      "epoch: 39 ,i: 450 ,Loss_D: 0.05808820575475693 ,Loss_G: 6.295134544372559 ,D(x): 0.9885720014572144 ,D(G(z)) 9.791937538513949\n",
      "epoch: 39 ,i: 500 ,Loss_D: 0.12669697403907776 ,Loss_G: 4.200738906860352 ,D(x): 0.8938047289848328 ,D(G(z)) 0.05802616875067847\n",
      "epoch: 39 ,i: 550 ,Loss_D: 0.03482799232006073 ,Loss_G: 5.438473701477051 ,D(x): 0.9842218160629272 ,D(G(z)) 1.8543708611178569\n",
      "epoch: 39 ,i: 600 ,Loss_D: 0.6240479946136475 ,Loss_G: 4.9669413566589355 ,D(x): 0.9764378666877747 ,D(G(z)) 25.028412970731967\n",
      "epoch: 39 ,i: 650 ,Loss_D: 0.10895606875419617 ,Loss_G: 5.4008355140686035 ,D(x): 0.9750281572341919 ,D(G(z)) 4.189424189828221\n",
      "epoch: 39 ,i: 700 ,Loss_D: 0.2864086329936981 ,Loss_G: 6.216918468475342 ,D(x): 0.973800539970398 ,D(G(z)) 54.40377364652593\n",
      "epoch: 39 ,i: 750 ,Loss_D: 0.18657264113426208 ,Loss_G: 6.111851692199707 ,D(x): 0.930079996585846 ,D(G(z)) 4.270847189843246\n",
      "epoch: 40 ,i: 0 ,Loss_D: 0.11547289788722992 ,Loss_G: 4.512938499450684 ,D(x): 0.9376136064529419 ,D(G(z)) 0.9059946610387501\n",
      "epoch: 40 ,i: 50 ,Loss_D: 0.19594836235046387 ,Loss_G: 4.6390509605407715 ,D(x): 0.9025552868843079 ,D(G(z)) 2.610893157509231\n",
      "epoch: 40 ,i: 100 ,Loss_D: 0.06798376142978668 ,Loss_G: 4.866351127624512 ,D(x): 0.987832248210907 ,D(G(z)) 3.4562407877537336\n",
      "epoch: 40 ,i: 150 ,Loss_D: 0.023732667788863182 ,Loss_G: 6.304388046264648 ,D(x): 0.9945950508117676 ,D(G(z)) 3.812885817986652\n",
      "epoch: 40 ,i: 200 ,Loss_D: 0.05778445303440094 ,Loss_G: 5.1740570068359375 ,D(x): 0.9651085138320923 ,D(G(z)) 1.034752324874355\n",
      "epoch: 40 ,i: 250 ,Loss_D: 0.04903336614370346 ,Loss_G: 5.377051830291748 ,D(x): 0.9856420755386353 ,D(G(z)) 3.2866592743443492\n",
      "epoch: 40 ,i: 300 ,Loss_D: 0.07776376605033875 ,Loss_G: 4.778700351715088 ,D(x): 0.9665279388427734 ,D(G(z)) 2.1416078804447496\n",
      "epoch: 40 ,i: 350 ,Loss_D: 0.07211929559707642 ,Loss_G: 5.340610980987549 ,D(x): 0.972826361656189 ,D(G(z)) 3.9655350260350044\n",
      "epoch: 40 ,i: 400 ,Loss_D: 0.02779347077012062 ,Loss_G: 6.499857425689697 ,D(x): 0.9924082159996033 ,D(G(z)) 3.238653319123621\n",
      "epoch: 40 ,i: 450 ,Loss_D: 0.0231611467897892 ,Loss_G: 5.611507415771484 ,D(x): 0.9862467050552368 ,D(G(z)) 0.8089881962191684\n",
      "epoch: 40 ,i: 500 ,Loss_D: 0.11034167557954788 ,Loss_G: 7.122342586517334 ,D(x): 0.9937919974327087 ,D(G(z)) 32.68423332976081\n",
      "epoch: 40 ,i: 550 ,Loss_D: 0.08391173183917999 ,Loss_G: 4.320069313049316 ,D(x): 0.9324100613594055 ,D(G(z)) 0.271748528455507\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 40 ,i: 600 ,Loss_D: 0.017893889918923378 ,Loss_G: 7.870868682861328 ,D(x): 0.9852092266082764 ,D(G(z)) 1.3922111279806235\n",
      "epoch: 40 ,i: 650 ,Loss_D: 0.041939325630664825 ,Loss_G: 7.228050231933594 ,D(x): 0.9949997663497925 ,D(G(z)) 15.886500730308281\n",
      "epoch: 40 ,i: 700 ,Loss_D: 0.07837698608636856 ,Loss_G: 7.128355026245117 ,D(x): 0.9905948638916016 ,D(G(z)) 18.507626331386025\n",
      "epoch: 40 ,i: 750 ,Loss_D: 0.01958593912422657 ,Loss_G: 6.021415710449219 ,D(x): 0.9917368292808533 ,D(G(z)) 1.486729374043428\n",
      "epoch: 41 ,i: 0 ,Loss_D: 0.3543665111064911 ,Loss_G: 10.967350006103516 ,D(x): 0.9970738887786865 ,D(G(z)) 6899.556583684202\n",
      "epoch: 41 ,i: 50 ,Loss_D: 0.08420601487159729 ,Loss_G: 7.575257301330566 ,D(x): 0.9933983087539673 ,D(G(z)) 59.66862479993698\n",
      "epoch: 41 ,i: 100 ,Loss_D: 0.021311311051249504 ,Loss_G: 6.798795700073242 ,D(x): 0.9930530786514282 ,D(G(z)) 4.830887208524715\n",
      "epoch: 41 ,i: 150 ,Loss_D: 0.01786298118531704 ,Loss_G: 5.558773040771484 ,D(x): 0.9919887781143188 ,D(G(z)) 1.267631686771218\n",
      "epoch: 41 ,i: 200 ,Loss_D: 0.04414132982492447 ,Loss_G: 5.828102111816406 ,D(x): 0.9659375548362732 ,D(G(z)) 0.4150123618605111\n",
      "epoch: 41 ,i: 250 ,Loss_D: 0.014181609265506268 ,Loss_G: 6.646427154541016 ,D(x): 0.9973067045211792 ,D(G(z)) 2.6127456480456424\n",
      "epoch: 41 ,i: 300 ,Loss_D: 0.015605921857059002 ,Loss_G: 6.855975151062012 ,D(x): 0.9918389320373535 ,D(G(z)) 2.2511433009449333\n",
      "epoch: 41 ,i: 350 ,Loss_D: 3.217195749282837 ,Loss_G: 0.7243116497993469 ,D(x): 0.22755779325962067 ,D(G(z)) 0.15175664095590688\n",
      "epoch: 41 ,i: 400 ,Loss_D: 0.32000839710235596 ,Loss_G: 4.587043762207031 ,D(x): 0.798576831817627 ,D(G(z)) 0.29768745678624364\n",
      "epoch: 41 ,i: 450 ,Loss_D: 0.36548975110054016 ,Loss_G: 6.8863420486450195 ,D(x): 0.9970959424972534 ,D(G(z)) 91.27211840118237\n",
      "epoch: 41 ,i: 500 ,Loss_D: 1.0405771732330322 ,Loss_G: 13.800436019897461 ,D(x): 0.9999568462371826 ,D(G(z)) 136544.7807414193\n",
      "epoch: 41 ,i: 550 ,Loss_D: 0.24389034509658813 ,Loss_G: 6.1582794189453125 ,D(x): 0.9613102674484253 ,D(G(z)) 28.06267987560715\n",
      "epoch: 41 ,i: 600 ,Loss_D: 0.024719301611185074 ,Loss_G: 9.097843170166016 ,D(x): 0.9860786199569702 ,D(G(z)) 10.784471329772455\n",
      "epoch: 41 ,i: 650 ,Loss_D: 0.38187339901924133 ,Loss_G: 2.8024837970733643 ,D(x): 0.7805232405662537 ,D(G(z)) 0.19728709456465562\n",
      "epoch: 41 ,i: 700 ,Loss_D: 0.09964526444673538 ,Loss_G: 5.650661468505859 ,D(x): 0.959283709526062 ,D(G(z)) 4.582474348273993\n",
      "epoch: 41 ,i: 750 ,Loss_D: 0.11388885974884033 ,Loss_G: 5.168402671813965 ,D(x): 0.915765643119812 ,D(G(z)) 0.678051246200774\n",
      "epoch: 42 ,i: 0 ,Loss_D: 0.09679731726646423 ,Loss_G: 4.387063503265381 ,D(x): 0.9391820430755615 ,D(G(z)) 0.4885966686205464\n",
      "epoch: 42 ,i: 50 ,Loss_D: 0.11222891509532928 ,Loss_G: 6.296498775482178 ,D(x): 0.9852054119110107 ,D(G(z)) 17.841099272308323\n",
      "epoch: 42 ,i: 100 ,Loss_D: 0.03431253507733345 ,Loss_G: 6.126069068908691 ,D(x): 0.9861195087432861 ,D(G(z)) 3.020187553551324\n",
      "epoch: 42 ,i: 150 ,Loss_D: 0.08839564025402069 ,Loss_G: 5.182735919952393 ,D(x): 0.9511260986328125 ,D(G(z)) 1.3937758971108736\n",
      "epoch: 42 ,i: 200 ,Loss_D: 0.060671381652355194 ,Loss_G: 5.3753204345703125 ,D(x): 0.9718213081359863 ,D(G(z)) 2.088854110309168\n",
      "epoch: 42 ,i: 250 ,Loss_D: 0.04964681342244148 ,Loss_G: 4.962325096130371 ,D(x): 0.992622435092926 ,D(G(z)) 2.6458646152606513\n",
      "epoch: 42 ,i: 300 ,Loss_D: 0.03264808654785156 ,Loss_G: 6.21650505065918 ,D(x): 0.9989892244338989 ,D(G(z)) 6.674410699629423\n",
      "epoch: 42 ,i: 350 ,Loss_D: 0.1667756736278534 ,Loss_G: 8.948751449584961 ,D(x): 0.9877828359603882 ,D(G(z)) 332.92537891363173\n",
      "epoch: 42 ,i: 400 ,Loss_D: 0.34256747364997864 ,Loss_G: 5.80061149597168 ,D(x): 0.7531784176826477 ,D(G(z)) 0.019290603537581347\n",
      "epoch: 42 ,i: 450 ,Loss_D: 0.027968522161245346 ,Loss_G: 5.101016044616699 ,D(x): 0.9821105003356934 ,D(G(z)) 0.6342166692459332\n",
      "epoch: 42 ,i: 500 ,Loss_D: 0.07530771195888519 ,Loss_G: 5.747689723968506 ,D(x): 0.973137378692627 ,D(G(z)) 4.8745489299288165\n",
      "epoch: 42 ,i: 550 ,Loss_D: 0.0785038024187088 ,Loss_G: 7.2143096923828125 ,D(x): 0.9971665143966675 ,D(G(z)) 42.18908952300814\n",
      "epoch: 42 ,i: 600 ,Loss_D: 1.6020481586456299 ,Loss_G: 8.46424674987793 ,D(x): 0.9861781597137451 ,D(G(z)) 830.2469992437957\n",
      "epoch: 42 ,i: 650 ,Loss_D: 0.04756932705640793 ,Loss_G: 5.424914836883545 ,D(x): 0.9864882230758667 ,D(G(z)) 2.638034659876905\n",
      "epoch: 42 ,i: 700 ,Loss_D: 0.11069392412900925 ,Loss_G: 5.239678382873535 ,D(x): 0.9147768020629883 ,D(G(z)) 0.20274876689329052\n",
      "epoch: 42 ,i: 750 ,Loss_D: 0.137199267745018 ,Loss_G: 6.964034080505371 ,D(x): 0.9626427292823792 ,D(G(z)) 22.31676286057013\n",
      "epoch: 43 ,i: 0 ,Loss_D: 0.09959417581558228 ,Loss_G: 6.464959144592285 ,D(x): 0.985410213470459 ,D(G(z)) 13.949756939278124\n",
      "epoch: 43 ,i: 50 ,Loss_D: 0.17466606199741364 ,Loss_G: 9.074012756347656 ,D(x): 0.9965901374816895 ,D(G(z)) 433.6026606785216\n",
      "epoch: 43 ,i: 100 ,Loss_D: 0.6203733682632446 ,Loss_G: 5.396288871765137 ,D(x): 0.6704254746437073 ,D(G(z)) 0.12015657980747996\n",
      "epoch: 43 ,i: 150 ,Loss_D: 0.24587640166282654 ,Loss_G: 6.753355503082275 ,D(x): 0.982591986656189 ,D(G(z)) 71.5183238594702\n",
      "epoch: 43 ,i: 200 ,Loss_D: 0.09076840430498123 ,Loss_G: 5.1180739402771 ,D(x): 0.927443265914917 ,D(G(z)) 0.37739694138179863\n",
      "epoch: 43 ,i: 250 ,Loss_D: 0.10924673080444336 ,Loss_G: 4.068314075469971 ,D(x): 0.9237022995948792 ,D(G(z)) 0.4552676918181442\n",
      "epoch: 43 ,i: 300 ,Loss_D: 0.0292997807264328 ,Loss_G: 5.582470893859863 ,D(x): 0.9842206239700317 ,D(G(z)) 1.3647709399989794\n",
      "epoch: 43 ,i: 350 ,Loss_D: 0.1311386227607727 ,Loss_G: 3.7088491916656494 ,D(x): 0.9043876528739929 ,D(G(z)) 0.1674134804255932\n",
      "epoch: 43 ,i: 400 ,Loss_D: 0.15034209191799164 ,Loss_G: 2.9735636711120605 ,D(x): 0.8893099427223206 ,D(G(z)) 0.07601003743110799\n",
      "epoch: 43 ,i: 450 ,Loss_D: 0.018917232751846313 ,Loss_G: 6.236370086669922 ,D(x): 0.9894254207611084 ,D(G(z)) 1.2774090777674907\n",
      "epoch: 43 ,i: 500 ,Loss_D: 0.07044694572687149 ,Loss_G: 6.153220176696777 ,D(x): 0.9785881042480469 ,D(G(z)) 10.272249470185105\n",
      "epoch: 43 ,i: 550 ,Loss_D: 0.010652724653482437 ,Loss_G: 6.513749122619629 ,D(x): 0.9965734481811523 ,D(G(z)) 1.695837338376412\n",
      "epoch: 43 ,i: 600 ,Loss_D: 0.11048666387796402 ,Loss_G: 7.900700569152832 ,D(x): 0.9162969589233398 ,D(G(z)) 1.15162351343469\n",
      "epoch: 43 ,i: 650 ,Loss_D: 0.043305352330207825 ,Loss_G: 7.27260684967041 ,D(x): 0.9781882166862488 ,D(G(z)) 8.522648072184934\n",
      "epoch: 43 ,i: 700 ,Loss_D: 0.2032528519630432 ,Loss_G: 6.681166648864746 ,D(x): 0.969025731086731 ,D(G(z)) 41.13131338061383\n",
      "epoch: 43 ,i: 750 ,Loss_D: 0.07304137200117111 ,Loss_G: 4.962211608886719 ,D(x): 0.9416460990905762 ,D(G(z)) 0.4427353861280666\n",
      "epoch: 44 ,i: 0 ,Loss_D: 0.2366335093975067 ,Loss_G: 4.815766334533691 ,D(x): 0.9544717073440552 ,D(G(z)) 7.441550145792918\n",
      "epoch: 44 ,i: 50 ,Loss_D: 0.05097433924674988 ,Loss_G: 6.244121074676514 ,D(x): 0.989699125289917 ,D(G(z)) 6.192600463869195\n",
      "epoch: 44 ,i: 100 ,Loss_D: 0.1283538043498993 ,Loss_G: 6.346355438232422 ,D(x): 0.9823883771896362 ,D(G(z)) 21.90990954967498\n",
      "epoch: 44 ,i: 150 ,Loss_D: 0.038421209901571274 ,Loss_G: 5.855224609375 ,D(x): 0.9788508415222168 ,D(G(z)) 1.0969781879636855\n",
      "epoch: 44 ,i: 200 ,Loss_D: 0.06291529536247253 ,Loss_G: 6.251448631286621 ,D(x): 0.9592995643615723 ,D(G(z)) 1.703293610601905\n",
      "epoch: 44 ,i: 250 ,Loss_D: 0.18396897614002228 ,Loss_G: 3.4400718212127686 ,D(x): 0.9063082933425903 ,D(G(z)) 0.998389942307726\n",
      "epoch: 44 ,i: 300 ,Loss_D: 0.14821979403495789 ,Loss_G: 2.7686800956726074 ,D(x): 0.9051980972290039 ,D(G(z)) 0.16069739272104921\n",
      "epoch: 44 ,i: 350 ,Loss_D: 0.067989781498909 ,Loss_G: 5.016806602478027 ,D(x): 0.942719578742981 ,D(G(z)) 0.2523368062985965\n",
      "epoch: 44 ,i: 400 ,Loss_D: 0.1232750415802002 ,Loss_G: 6.085365295410156 ,D(x): 0.9845666885375977 ,D(G(z)) 18.340170357580075\n",
      "epoch: 44 ,i: 450 ,Loss_D: 0.03793427720665932 ,Loss_G: 6.577834129333496 ,D(x): 0.9716397523880005 ,D(G(z)) 1.5134136993407055\n",
      "epoch: 44 ,i: 500 ,Loss_D: 0.04808126017451286 ,Loss_G: 6.002870559692383 ,D(x): 0.9926400184631348 ,D(G(z)) 6.178481400904313\n",
      "epoch: 44 ,i: 550 ,Loss_D: 0.022900793701410294 ,Loss_G: 5.871885299682617 ,D(x): 0.9864068031311035 ,D(G(z)) 1.2100910836464438\n",
      "epoch: 44 ,i: 600 ,Loss_D: 0.03427330031991005 ,Loss_G: 5.20271635055542 ,D(x): 0.9775768518447876 ,D(G(z)) 0.6388326685996493\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 44 ,i: 650 ,Loss_D: 0.3417759835720062 ,Loss_G: 5.929291725158691 ,D(x): 0.9970369935035706 ,D(G(z)) 40.4859598817713\n",
      "epoch: 44 ,i: 700 ,Loss_D: 0.05324584245681763 ,Loss_G: 5.078763008117676 ,D(x): 0.9985297918319702 ,D(G(z)) 2.0164980516658217\n",
      "epoch: 44 ,i: 750 ,Loss_D: 0.08593256771564484 ,Loss_G: 6.068978309631348 ,D(x): 0.9950757026672363 ,D(G(z)) 8.66334667878052\n",
      "epoch: 45 ,i: 0 ,Loss_D: 2.130093574523926 ,Loss_G: 11.828512191772461 ,D(x): 0.9992064833641052 ,D(G(z)) 10848.439992657597\n",
      "epoch: 45 ,i: 50 ,Loss_D: 0.22653773427009583 ,Loss_G: 2.1582159996032715 ,D(x): 0.8294040560722351 ,D(G(z)) 0.02294937715898154\n",
      "epoch: 45 ,i: 100 ,Loss_D: 0.09326833486557007 ,Loss_G: 6.8472089767456055 ,D(x): 0.9913133382797241 ,D(G(z)) 21.148267129927056\n",
      "epoch: 45 ,i: 150 ,Loss_D: 0.0362108089029789 ,Loss_G: 5.536844253540039 ,D(x): 0.982473611831665 ,D(G(z)) 1.5913905415081702\n",
      "epoch: 45 ,i: 200 ,Loss_D: 4.5020880699157715 ,Loss_G: 1.1782546043395996 ,D(x): 0.031933315098285675 ,D(G(z)) 0.0006913582674769157\n",
      "epoch: 45 ,i: 250 ,Loss_D: 0.015218514949083328 ,Loss_G: 4.664437294006348 ,D(x): 0.996519923210144 ,D(G(z)) 0.26316316715684956\n",
      "epoch: 45 ,i: 300 ,Loss_D: 0.045863132923841476 ,Loss_G: 5.974730014801025 ,D(x): 0.9681627154350281 ,D(G(z)) 1.5842325634615793\n",
      "epoch: 45 ,i: 350 ,Loss_D: 0.14298105239868164 ,Loss_G: 4.270694732666016 ,D(x): 0.93207848072052 ,D(G(z)) 1.7913347024809585\n",
      "epoch: 45 ,i: 400 ,Loss_D: 0.06280562281608582 ,Loss_G: 6.307451248168945 ,D(x): 0.9970481991767883 ,D(G(z)) 13.86629024705086\n",
      "epoch: 45 ,i: 450 ,Loss_D: 0.026998944580554962 ,Loss_G: 6.234750747680664 ,D(x): 0.9834972620010376 ,D(G(z)) 1.7341069003826688\n",
      "epoch: 45 ,i: 500 ,Loss_D: 0.08717328310012817 ,Loss_G: 4.917757034301758 ,D(x): 0.9337716698646545 ,D(G(z)) 0.2446576264430385\n",
      "epoch: 45 ,i: 550 ,Loss_D: 0.02976791188120842 ,Loss_G: 5.764552116394043 ,D(x): 0.9828214645385742 ,D(G(z)) 1.2381716215896914\n",
      "epoch: 45 ,i: 600 ,Loss_D: 0.06473726779222488 ,Loss_G: 5.866587162017822 ,D(x): 0.9901565313339233 ,D(G(z)) 7.200472084520527\n",
      "epoch: 45 ,i: 650 ,Loss_D: 0.05379465967416763 ,Loss_G: 6.280910968780518 ,D(x): 0.9914829730987549 ,D(G(z)) 8.413172820596786\n",
      "epoch: 45 ,i: 700 ,Loss_D: 0.6742264032363892 ,Loss_G: 6.390380382537842 ,D(x): 0.9794986248016357 ,D(G(z)) 41.37118296782275\n",
      "epoch: 45 ,i: 750 ,Loss_D: 0.05084601789712906 ,Loss_G: 6.160628795623779 ,D(x): 0.9843109250068665 ,D(G(z)) 6.507415822512792\n",
      "epoch: 46 ,i: 0 ,Loss_D: 0.07521218806505203 ,Loss_G: 7.3592634201049805 ,D(x): 0.9893622398376465 ,D(G(z)) 33.38153832239969\n",
      "epoch: 46 ,i: 50 ,Loss_D: 0.09837047755718231 ,Loss_G: 4.014676094055176 ,D(x): 0.9215875864028931 ,D(G(z)) 0.14093972718990688\n",
      "epoch: 46 ,i: 100 ,Loss_D: 0.044129885733127594 ,Loss_G: 5.229556560516357 ,D(x): 0.9680535793304443 ,D(G(z)) 0.43336754632729396\n",
      "epoch: 46 ,i: 150 ,Loss_D: 0.03971396014094353 ,Loss_G: 6.443592548370361 ,D(x): 0.9909757971763611 ,D(G(z)) 5.2950767212534195\n",
      "epoch: 46 ,i: 200 ,Loss_D: 0.02750750258564949 ,Loss_G: 5.020367622375488 ,D(x): 0.9889734983444214 ,D(G(z)) 0.932303683563365\n",
      "epoch: 46 ,i: 250 ,Loss_D: 0.10406074672937393 ,Loss_G: 4.3197455406188965 ,D(x): 0.9192370176315308 ,D(G(z)) 0.13347056932467155\n",
      "epoch: 46 ,i: 300 ,Loss_D: 0.043359946459531784 ,Loss_G: 5.66225004196167 ,D(x): 0.9833559393882751 ,D(G(z)) 2.611718241330349\n",
      "epoch: 46 ,i: 350 ,Loss_D: 0.05160592496395111 ,Loss_G: 5.621976852416992 ,D(x): 0.9899011850357056 ,D(G(z)) 4.880755640738651\n",
      "epoch: 46 ,i: 400 ,Loss_D: 0.12626397609710693 ,Loss_G: 3.0454113483428955 ,D(x): 0.9141955375671387 ,D(G(z)) 0.0997133003837296\n",
      "epoch: 46 ,i: 450 ,Loss_D: 0.16012489795684814 ,Loss_G: 4.250152587890625 ,D(x): 0.9642729163169861 ,D(G(z)) 3.3078604670769125\n",
      "epoch: 46 ,i: 500 ,Loss_D: 0.04796801507472992 ,Loss_G: 6.508520603179932 ,D(x): 0.9828276634216309 ,D(G(z)) 4.729742810587079\n",
      "epoch: 46 ,i: 550 ,Loss_D: 0.09440931677818298 ,Loss_G: 6.560990810394287 ,D(x): 0.9388097524642944 ,D(G(z)) 1.3719248273078581\n",
      "epoch: 46 ,i: 600 ,Loss_D: 0.0865650400519371 ,Loss_G: 5.5823516845703125 ,D(x): 0.9308463335037231 ,D(G(z)) 0.6708532321184378\n",
      "epoch: 46 ,i: 650 ,Loss_D: 5.322165489196777 ,Loss_G: 10.155397415161133 ,D(x): 0.9999558329582214 ,D(G(z)) 3710.2784798023804\n",
      "epoch: 46 ,i: 700 ,Loss_D: 1.5004727840423584 ,Loss_G: 6.006396293640137 ,D(x): 0.9814561605453491 ,D(G(z)) 72.04403846002134\n",
      "epoch: 46 ,i: 750 ,Loss_D: 0.16739465296268463 ,Loss_G: 4.853916645050049 ,D(x): 0.9604392051696777 ,D(G(z)) 5.930978663298187\n",
      "epoch: 47 ,i: 0 ,Loss_D: 0.08500280976295471 ,Loss_G: 5.889444828033447 ,D(x): 0.9956387877464294 ,D(G(z)) 6.630347878227498\n",
      "epoch: 47 ,i: 50 ,Loss_D: 0.08264888823032379 ,Loss_G: 4.746951103210449 ,D(x): 0.9357239603996277 ,D(G(z)) 0.29796584084975164\n",
      "epoch: 47 ,i: 100 ,Loss_D: 0.06619014590978622 ,Loss_G: 4.798429489135742 ,D(x): 0.9575014710426331 ,D(G(z)) 0.6610002112606568\n",
      "epoch: 47 ,i: 150 ,Loss_D: 0.05421395227313042 ,Loss_G: 5.216094017028809 ,D(x): 0.9811577796936035 ,D(G(z)) 3.0002611857971493\n",
      "epoch: 47 ,i: 200 ,Loss_D: 0.15961526334285736 ,Loss_G: 5.020730972290039 ,D(x): 0.8739567995071411 ,D(G(z)) 0.21721099768841917\n",
      "epoch: 47 ,i: 250 ,Loss_D: 0.07595750689506531 ,Loss_G: 5.650257110595703 ,D(x): 0.9720318913459778 ,D(G(z)) 5.263942936982438\n",
      "epoch: 47 ,i: 300 ,Loss_D: 0.11451046913862228 ,Loss_G: 4.754706382751465 ,D(x): 0.909652054309845 ,D(G(z)) 0.15141590599743565\n",
      "epoch: 47 ,i: 350 ,Loss_D: 0.02578279748558998 ,Loss_G: 5.71837854385376 ,D(x): 0.9946771264076233 ,D(G(z)) 2.181818876571365\n",
      "epoch: 47 ,i: 400 ,Loss_D: 0.029498204588890076 ,Loss_G: 5.882135391235352 ,D(x): 0.9836592674255371 ,D(G(z)) 1.3051442584139301\n",
      "epoch: 47 ,i: 450 ,Loss_D: 0.05841369181871414 ,Loss_G: 4.995902061462402 ,D(x): 0.9615474939346313 ,D(G(z)) 0.7142735561130169\n",
      "epoch: 47 ,i: 500 ,Loss_D: 0.05244665592908859 ,Loss_G: 4.856607913970947 ,D(x): 0.9584348201751709 ,D(G(z)) 0.3178289830683675\n",
      "epoch: 47 ,i: 550 ,Loss_D: 0.1937854140996933 ,Loss_G: 6.201908111572266 ,D(x): 0.9391046762466431 ,D(G(z)) 20.297589563757327\n",
      "epoch: 47 ,i: 600 ,Loss_D: 0.019150082021951675 ,Loss_G: 8.373236656188965 ,D(x): 0.9861596822738647 ,D(G(z)) 9.657620266367232\n",
      "epoch: 47 ,i: 650 ,Loss_D: 1.3984110355377197 ,Loss_G: 14.977503776550293 ,D(x): 0.9998148679733276 ,D(G(z)) 466425.69124498713\n",
      "epoch: 47 ,i: 700 ,Loss_D: 0.18130341172218323 ,Loss_G: 3.7800886631011963 ,D(x): 0.9172760248184204 ,D(G(z)) 1.1031620647820937\n",
      "epoch: 47 ,i: 750 ,Loss_D: 0.043018318712711334 ,Loss_G: 7.082637786865234 ,D(x): 0.9971066117286682 ,D(G(z)) 13.908899588032384\n",
      "epoch: 48 ,i: 0 ,Loss_D: 8.06814193725586 ,Loss_G: 17.3681640625 ,D(x): 0.9999999403953552 ,D(G(z)) 715923.5672282471\n",
      "epoch: 48 ,i: 50 ,Loss_D: 0.13471302390098572 ,Loss_G: 4.604132652282715 ,D(x): 0.8995227813720703 ,D(G(z)) 0.30189958811276046\n",
      "epoch: 48 ,i: 100 ,Loss_D: 0.3489559590816498 ,Loss_G: 9.791765213012695 ,D(x): 0.997393786907196 ,D(G(z)) 2430.6315216649114\n",
      "epoch: 48 ,i: 150 ,Loss_D: 0.0355098582804203 ,Loss_G: 5.807522296905518 ,D(x): 0.9807498455047607 ,D(G(z)) 1.895700392292531\n",
      "epoch: 48 ,i: 200 ,Loss_D: 0.2790099084377289 ,Loss_G: 10.115821838378906 ,D(x): 0.9995534420013428 ,D(G(z)) 2458.93342428759\n",
      "epoch: 48 ,i: 250 ,Loss_D: 0.021085744723677635 ,Loss_G: 7.0253071784973145 ,D(x): 0.9833370447158813 ,D(G(z)) 1.4871640711692755\n",
      "epoch: 48 ,i: 300 ,Loss_D: 0.08110231161117554 ,Loss_G: 5.4894256591796875 ,D(x): 0.9747899770736694 ,D(G(z)) 4.542242827087095\n",
      "epoch: 48 ,i: 350 ,Loss_D: 0.03999672085046768 ,Loss_G: 5.3280792236328125 ,D(x): 0.9791350960731506 ,D(G(z)) 0.9574744711339274\n",
      "epoch: 48 ,i: 400 ,Loss_D: 0.10680492222309113 ,Loss_G: 5.543813228607178 ,D(x): 0.9177942276000977 ,D(G(z)) 0.4930889701416396\n",
      "epoch: 48 ,i: 450 ,Loss_D: 0.04238997399806976 ,Loss_G: 6.017071723937988 ,D(x): 0.9911520481109619 ,D(G(z)) 3.5577477970928286\n",
      "epoch: 48 ,i: 500 ,Loss_D: 0.17128422856330872 ,Loss_G: 6.894479274749756 ,D(x): 0.9504703879356384 ,D(G(z)) 15.17154102597776\n",
      "epoch: 48 ,i: 550 ,Loss_D: 0.06483707576990128 ,Loss_G: 5.455005645751953 ,D(x): 0.9490101337432861 ,D(G(z)) 0.4371971078007843\n",
      "epoch: 48 ,i: 600 ,Loss_D: 0.018518012017011642 ,Loss_G: 5.750733375549316 ,D(x): 0.9949133396148682 ,D(G(z)) 1.1202375392325865\n",
      "epoch: 48 ,i: 650 ,Loss_D: 0.06139620393514633 ,Loss_G: 6.283502578735352 ,D(x): 0.948764443397522 ,D(G(z)) 0.4984378339463886\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 48 ,i: 700 ,Loss_D: 0.052094295620918274 ,Loss_G: 6.9983744621276855 ,D(x): 0.9668866395950317 ,D(G(z)) 4.566008540355679\n",
      "epoch: 48 ,i: 750 ,Loss_D: 0.07667528837919235 ,Loss_G: 6.579568386077881 ,D(x): 0.9864152669906616 ,D(G(z)) 10.95843171449908\n",
      "epoch: 49 ,i: 0 ,Loss_D: 0.2514944076538086 ,Loss_G: 7.246241569519043 ,D(x): 0.9995595216751099 ,D(G(z)) 76.21002538365947\n",
      "epoch: 49 ,i: 50 ,Loss_D: 0.023481447249650955 ,Loss_G: 6.282539367675781 ,D(x): 0.9891961216926575 ,D(G(z)) 2.158203195348478\n",
      "epoch: 49 ,i: 100 ,Loss_D: 0.02973073162138462 ,Loss_G: 5.802299499511719 ,D(x): 0.9879293441772461 ,D(G(z)) 2.1109582337546775\n",
      "epoch: 49 ,i: 150 ,Loss_D: 0.03998085856437683 ,Loss_G: 8.261272430419922 ,D(x): 0.9703959226608276 ,D(G(z)) 7.026414915561444\n",
      "epoch: 49 ,i: 200 ,Loss_D: 0.015512421727180481 ,Loss_G: 6.990872859954834 ,D(x): 0.996891975402832 ,D(G(z)) 3.5837074344383137\n",
      "epoch: 49 ,i: 250 ,Loss_D: 0.02133733034133911 ,Loss_G: 7.299835681915283 ,D(x): 0.9923335909843445 ,D(G(z)) 5.391987299565055\n",
      "epoch: 49 ,i: 300 ,Loss_D: 0.09953057765960693 ,Loss_G: 4.2499895095825195 ,D(x): 0.9476451277732849 ,D(G(z)) 1.2857286111523485\n",
      "epoch: 49 ,i: 350 ,Loss_D: 0.053919244557619095 ,Loss_G: 4.912440776824951 ,D(x): 0.9653946757316589 ,D(G(z)) 0.8033033218198644\n",
      "epoch: 49 ,i: 400 ,Loss_D: 0.3636274039745331 ,Loss_G: 2.336334705352783 ,D(x): 0.778847873210907 ,D(G(z)) 0.03889352731040803\n",
      "epoch: 49 ,i: 450 ,Loss_D: 2.2726798057556152 ,Loss_G: 9.343400955200195 ,D(x): 0.9999797940254211 ,D(G(z)) 1269.8300148414885\n",
      "epoch: 49 ,i: 500 ,Loss_D: 0.11248168349266052 ,Loss_G: 6.174687385559082 ,D(x): 0.9382407665252686 ,D(G(z)) 4.381568777680632\n",
      "epoch: 49 ,i: 550 ,Loss_D: 0.04600223898887634 ,Loss_G: 7.38099479675293 ,D(x): 0.971003532409668 ,D(G(z)) 5.636192877548896\n",
      "epoch: 49 ,i: 600 ,Loss_D: 0.26838165521621704 ,Loss_G: 4.112995147705078 ,D(x): 0.836334228515625 ,D(G(z)) 0.694844063459681\n",
      "epoch: 49 ,i: 650 ,Loss_D: 0.16614657640457153 ,Loss_G: 5.335424900054932 ,D(x): 0.9906933307647705 ,D(G(z)) 12.412393852821763\n",
      "epoch: 49 ,i: 700 ,Loss_D: 0.06022459268569946 ,Loss_G: 6.099132537841797 ,D(x): 0.9529592990875244 ,D(G(z)) 1.0872146912100564\n",
      "epoch: 49 ,i: 750 ,Loss_D: 0.01422675047069788 ,Loss_G: 7.16070556640625 ,D(x): 0.9924980401992798 ,D(G(z)) 2.0517768476914395\n",
      "epoch: 50 ,i: 0 ,Loss_D: 0.0724143534898758 ,Loss_G: 5.298941612243652 ,D(x): 0.9751948118209839 ,D(G(z)) 2.792025406194258\n",
      "epoch: 50 ,i: 50 ,Loss_D: 0.10617128759622574 ,Loss_G: 4.760709285736084 ,D(x): 0.9127399325370789 ,D(G(z)) 0.2558958235782914\n",
      "epoch: 50 ,i: 100 ,Loss_D: 0.04214818775653839 ,Loss_G: 5.017729759216309 ,D(x): 0.9823131561279297 ,D(G(z)) 1.3011807414711087\n",
      "epoch: 50 ,i: 150 ,Loss_D: 0.05782058835029602 ,Loss_G: 5.298516273498535 ,D(x): 0.9848005771636963 ,D(G(z)) 3.3510625714167075\n",
      "epoch: 50 ,i: 200 ,Loss_D: 0.05835369601845741 ,Loss_G: 5.17427921295166 ,D(x): 0.9682726860046387 ,D(G(z)) 1.659461177651807\n",
      "epoch: 50 ,i: 250 ,Loss_D: 0.060222137719392776 ,Loss_G: 6.238604545593262 ,D(x): 0.9664027690887451 ,D(G(z)) 3.1358790369811023\n",
      "epoch: 50 ,i: 300 ,Loss_D: 0.025984924286603928 ,Loss_G: 6.768060684204102 ,D(x): 0.9830044507980347 ,D(G(z)) 2.7478781568753172\n",
      "epoch: 50 ,i: 350 ,Loss_D: 0.025349464267492294 ,Loss_G: 6.089986801147461 ,D(x): 0.9919703006744385 ,D(G(z)) 2.3487617909001375\n",
      "epoch: 50 ,i: 400 ,Loss_D: 0.0752849280834198 ,Loss_G: 6.097541809082031 ,D(x): 0.9817408919334412 ,D(G(z)) 10.72399951097474\n",
      "epoch: 50 ,i: 450 ,Loss_D: 0.03762824088335037 ,Loss_G: 6.208185195922852 ,D(x): 0.9865654706954956 ,D(G(z)) 3.486671930953986\n",
      "epoch: 50 ,i: 500 ,Loss_D: 0.0499088391661644 ,Loss_G: 5.119332790374756 ,D(x): 0.9950329065322876 ,D(G(z)) 2.5235215342478914\n",
      "epoch: 50 ,i: 550 ,Loss_D: 0.02654084376990795 ,Loss_G: 7.217509746551514 ,D(x): 0.9887835383415222 ,D(G(z)) 4.458742835731038\n",
      "epoch: 50 ,i: 600 ,Loss_D: 0.024322105571627617 ,Loss_G: 6.307170867919922 ,D(x): 0.9985378384590149 ,D(G(z)) 4.43432485878379\n",
      "epoch: 50 ,i: 650 ,Loss_D: 0.5989710092544556 ,Loss_G: 2.683345317840576 ,D(x): 0.784786581993103 ,D(G(z)) 0.8967748839783966\n",
      "epoch: 50 ,i: 700 ,Loss_D: 0.28135669231414795 ,Loss_G: 4.8029632568359375 ,D(x): 0.8682942390441895 ,D(G(z)) 2.295857609108704\n",
      "epoch: 50 ,i: 750 ,Loss_D: 0.07742128521203995 ,Loss_G: 6.975362777709961 ,D(x): 0.9405820369720459 ,D(G(z)) 1.9629233507932815\n",
      "epoch: 51 ,i: 0 ,Loss_D: 0.11103906482458115 ,Loss_G: 4.375743865966797 ,D(x): 0.9344031810760498 ,D(G(z)) 0.8383180925291542\n",
      "epoch: 51 ,i: 50 ,Loss_D: 0.3750357925891876 ,Loss_G: 10.286201477050781 ,D(x): 0.989931046962738 ,D(G(z)) 2276.0642572312204\n",
      "epoch: 51 ,i: 100 ,Loss_D: 0.15650802850723267 ,Loss_G: 5.020397186279297 ,D(x): 0.8982212543487549 ,D(G(z)) 0.7162637346955806\n",
      "epoch: 51 ,i: 150 ,Loss_D: 0.04326021298766136 ,Loss_G: 6.11970329284668 ,D(x): 0.9827327132225037 ,D(G(z)) 3.380472327981403\n",
      "epoch: 51 ,i: 200 ,Loss_D: 0.18097908794879913 ,Loss_G: 5.4770307540893555 ,D(x): 0.9662922620773315 ,D(G(z)) 8.827233515501321\n",
      "epoch: 51 ,i: 250 ,Loss_D: 0.2046956568956375 ,Loss_G: 3.5997815132141113 ,D(x): 0.8685240745544434 ,D(G(z)) 0.2649576046061962\n",
      "epoch: 51 ,i: 300 ,Loss_D: 0.03548726439476013 ,Loss_G: 6.130318641662598 ,D(x): 0.9825775623321533 ,D(G(z)) 2.257868955955888\n",
      "epoch: 51 ,i: 350 ,Loss_D: 0.08466710150241852 ,Loss_G: 7.898818016052246 ,D(x): 0.9649757146835327 ,D(G(z)) 17.18941971743422\n",
      "epoch: 51 ,i: 400 ,Loss_D: 0.05006466433405876 ,Loss_G: 6.1516008377075195 ,D(x): 0.9932669401168823 ,D(G(z)) 6.551468246935125\n",
      "epoch: 51 ,i: 450 ,Loss_D: 0.02311774156987667 ,Loss_G: 6.123741626739502 ,D(x): 0.9968118667602539 ,D(G(z)) 3.7093101371575026\n",
      "epoch: 51 ,i: 500 ,Loss_D: 0.15086627006530762 ,Loss_G: 4.6657795906066895 ,D(x): 0.9274663925170898 ,D(G(z)) 1.8671008192850154\n",
      "epoch: 51 ,i: 550 ,Loss_D: 0.06235431134700775 ,Loss_G: 5.134039402008057 ,D(x): 0.9721119403839111 ,D(G(z)) 1.9280560682897683\n",
      "epoch: 51 ,i: 600 ,Loss_D: 0.10492503643035889 ,Loss_G: 3.7883217334747314 ,D(x): 0.9159601926803589 ,D(G(z)) 0.05581790132500769\n",
      "epoch: 51 ,i: 650 ,Loss_D: 0.07473853975534439 ,Loss_G: 6.645819664001465 ,D(x): 0.9944300651550293 ,D(G(z)) 21.46859962830662\n",
      "epoch: 51 ,i: 700 ,Loss_D: 0.024242334067821503 ,Loss_G: 6.789981365203857 ,D(x): 0.9876660108566284 ,D(G(z)) 3.494287511374489\n",
      "epoch: 51 ,i: 750 ,Loss_D: 0.032101426273584366 ,Loss_G: 5.743963241577148 ,D(x): 0.9924980998039246 ,D(G(z)) 2.4615869677725404\n",
      "epoch: 52 ,i: 0 ,Loss_D: 8.236512184143066 ,Loss_G: 11.431793212890625 ,D(x): 0.9999992847442627 ,D(G(z)) 23525.855274680012\n",
      "epoch: 52 ,i: 50 ,Loss_D: 0.06412585079669952 ,Loss_G: 4.656047821044922 ,D(x): 0.964756965637207 ,D(G(z)) 0.6071300694440377\n",
      "epoch: 52 ,i: 100 ,Loss_D: 0.12234316766262054 ,Loss_G: 4.267960548400879 ,D(x): 0.9522474408149719 ,D(G(z)) 1.4878333730080346\n",
      "epoch: 52 ,i: 150 ,Loss_D: 0.07529374957084656 ,Loss_G: 4.75431489944458 ,D(x): 0.9687478542327881 ,D(G(z)) 1.909490063768419\n",
      "epoch: 52 ,i: 200 ,Loss_D: 0.11450336873531342 ,Loss_G: 5.090022563934326 ,D(x): 0.9404710531234741 ,D(G(z)) 1.4977528607925852\n",
      "epoch: 52 ,i: 250 ,Loss_D: 0.055508751422166824 ,Loss_G: 4.979030609130859 ,D(x): 0.9690563082695007 ,D(G(z)) 0.9602243319142197\n",
      "epoch: 52 ,i: 300 ,Loss_D: 0.024849142879247665 ,Loss_G: 5.951704978942871 ,D(x): 0.9925327301025391 ,D(G(z)) 2.466016763547181\n",
      "epoch: 52 ,i: 350 ,Loss_D: 0.030196906998753548 ,Loss_G: 6.794150352478027 ,D(x): 0.9840247631072998 ,D(G(z)) 2.629376693914056\n",
      "epoch: 52 ,i: 400 ,Loss_D: 0.12163468450307846 ,Loss_G: 4.420754909515381 ,D(x): 0.9877725839614868 ,D(G(z)) 3.340594761639394\n",
      "epoch: 52 ,i: 450 ,Loss_D: 0.04278199002146721 ,Loss_G: 6.390409469604492 ,D(x): 0.9799549579620361 ,D(G(z)) 4.749041552248343\n",
      "epoch: 52 ,i: 500 ,Loss_D: 0.02189631201326847 ,Loss_G: 6.48897647857666 ,D(x): 0.9878811240196228 ,D(G(z)) 2.160353867637171\n",
      "epoch: 52 ,i: 550 ,Loss_D: 0.03657635301351547 ,Loss_G: 7.126203536987305 ,D(x): 0.9949325323104858 ,D(G(z)) 11.167744518441081\n",
      "epoch: 52 ,i: 600 ,Loss_D: 0.019331520423293114 ,Loss_G: 6.354362487792969 ,D(x): 0.9901450872421265 ,D(G(z)) 1.7146905611496703\n",
      "epoch: 52 ,i: 650 ,Loss_D: 0.029314659535884857 ,Loss_G: 6.777118682861328 ,D(x): 0.985384464263916 ,D(G(z)) 1.959916845290311\n",
      "epoch: 52 ,i: 700 ,Loss_D: 0.02741185948252678 ,Loss_G: 6.338830947875977 ,D(x): 0.9950000643730164 ,D(G(z)) 5.587862245568072\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 52 ,i: 750 ,Loss_D: 0.01064857468008995 ,Loss_G: 5.974699020385742 ,D(x): 0.9963793754577637 ,D(G(z)) 1.291237997776277\n",
      "epoch: 53 ,i: 0 ,Loss_D: 0.021237313747406006 ,Loss_G: 6.388454914093018 ,D(x): 0.9835931062698364 ,D(G(z)) 0.8326205211280799\n",
      "epoch: 53 ,i: 50 ,Loss_D: 0.957718551158905 ,Loss_G: 3.111515522003174 ,D(x): 0.7715510725975037 ,D(G(z)) 1.5476060393461484\n",
      "epoch: 53 ,i: 100 ,Loss_D: 0.2649252414703369 ,Loss_G: 4.251032829284668 ,D(x): 0.8790415525436401 ,D(G(z)) 2.667652863604247\n",
      "epoch: 53 ,i: 150 ,Loss_D: 0.8111559152603149 ,Loss_G: 1.2470424175262451 ,D(x): 0.6798491477966309 ,D(G(z)) 0.46965986091882234\n",
      "epoch: 53 ,i: 200 ,Loss_D: 0.21439552307128906 ,Loss_G: 5.250992298126221 ,D(x): 0.9249715805053711 ,D(G(z)) 6.573329782326533\n",
      "epoch: 53 ,i: 250 ,Loss_D: 0.048370976001024246 ,Loss_G: 6.350741386413574 ,D(x): 0.9694180488586426 ,D(G(z)) 1.6596329854170375\n",
      "epoch: 53 ,i: 300 ,Loss_D: 0.05911055952310562 ,Loss_G: 6.5921950340271 ,D(x): 0.9787394404411316 ,D(G(z)) 6.281065605371609\n",
      "epoch: 53 ,i: 350 ,Loss_D: 0.4866181015968323 ,Loss_G: 2.008671760559082 ,D(x): 0.6873900890350342 ,D(G(z)) 0.026997539001907562\n",
      "epoch: 53 ,i: 400 ,Loss_D: 0.0574435256421566 ,Loss_G: 5.617426872253418 ,D(x): 0.967758297920227 ,D(G(z)) 1.3900793797067648\n",
      "epoch: 53 ,i: 450 ,Loss_D: 0.08116020262241364 ,Loss_G: 4.791934967041016 ,D(x): 0.985303521156311 ,D(G(z)) 3.1828183002308856\n",
      "epoch: 53 ,i: 500 ,Loss_D: 0.06208541616797447 ,Loss_G: 5.593277931213379 ,D(x): 0.9700084924697876 ,D(G(z)) 1.230082215031984\n",
      "epoch: 53 ,i: 550 ,Loss_D: 0.04126153886318207 ,Loss_G: 6.256252288818359 ,D(x): 0.983339786529541 ,D(G(z)) 3.55849375435388\n",
      "epoch: 53 ,i: 600 ,Loss_D: 0.11062276363372803 ,Loss_G: 4.614106178283691 ,D(x): 0.9156600832939148 ,D(G(z)) 0.3472100720914372\n",
      "epoch: 53 ,i: 650 ,Loss_D: 0.09532932192087173 ,Loss_G: 6.329372882843018 ,D(x): 0.9738057851791382 ,D(G(z)) 8.369753846645981\n",
      "epoch: 53 ,i: 700 ,Loss_D: 0.07019220292568207 ,Loss_G: 5.888262748718262 ,D(x): 0.959325909614563 ,D(G(z)) 2.280350618142131\n",
      "epoch: 53 ,i: 750 ,Loss_D: 0.05494871735572815 ,Loss_G: 5.362261772155762 ,D(x): 0.9774857759475708 ,D(G(z)) 2.492009335057979\n",
      "epoch: 54 ,i: 0 ,Loss_D: 0.06313455104827881 ,Loss_G: 6.696566581726074 ,D(x): 0.9958726167678833 ,D(G(z)) 13.885580086260108\n",
      "epoch: 54 ,i: 50 ,Loss_D: 0.01939469575881958 ,Loss_G: 6.708193778991699 ,D(x): 0.9851495623588562 ,D(G(z)) 0.8927067057231545\n",
      "epoch: 54 ,i: 100 ,Loss_D: 0.07411085069179535 ,Loss_G: 5.5209455490112305 ,D(x): 0.9702140092849731 ,D(G(z)) 2.319672334540052\n",
      "epoch: 54 ,i: 150 ,Loss_D: 0.06047748401761055 ,Loss_G: 6.751335620880127 ,D(x): 0.9933996200561523 ,D(G(z)) 12.32817107887791\n",
      "epoch: 54 ,i: 200 ,Loss_D: 0.04775824397802353 ,Loss_G: 7.026735305786133 ,D(x): 0.9587242603302002 ,D(G(z)) 1.557561783922862\n",
      "epoch: 54 ,i: 250 ,Loss_D: 0.01936531811952591 ,Loss_G: 7.650413513183594 ,D(x): 0.9833793640136719 ,D(G(z)) 1.1057140240998324\n",
      "epoch: 54 ,i: 300 ,Loss_D: 0.033598724752664566 ,Loss_G: 7.229045867919922 ,D(x): 0.9985887408256531 ,D(G(z)) 13.100553833894057\n",
      "epoch: 54 ,i: 350 ,Loss_D: 0.029347680509090424 ,Loss_G: 6.80528450012207 ,D(x): 0.9945553541183472 ,D(G(z)) 7.858411024679628\n",
      "epoch: 54 ,i: 400 ,Loss_D: 1.4336488246917725 ,Loss_G: 6.196314811706543 ,D(x): 0.9918796420097351 ,D(G(z)) 106.00795508710296\n",
      "epoch: 54 ,i: 450 ,Loss_D: 0.04922698438167572 ,Loss_G: 7.404749870300293 ,D(x): 0.9924836158752441 ,D(G(z)) 20.21913043821009\n",
      "epoch: 54 ,i: 500 ,Loss_D: 0.13334712386131287 ,Loss_G: 5.389641284942627 ,D(x): 0.924805760383606 ,D(G(z)) 2.17364977278683\n",
      "epoch: 54 ,i: 550 ,Loss_D: 0.051238007843494415 ,Loss_G: 5.79007625579834 ,D(x): 0.9783680438995361 ,D(G(z)) 3.6266166069852104\n",
      "epoch: 54 ,i: 600 ,Loss_D: 0.6364349126815796 ,Loss_G: 1.148618459701538 ,D(x): 0.6513553857803345 ,D(G(z)) 0.15151028607175637\n",
      "epoch: 54 ,i: 650 ,Loss_D: 0.1449105441570282 ,Loss_G: 6.2458953857421875 ,D(x): 0.9750174880027771 ,D(G(z)) 15.61123239023356\n",
      "epoch: 54 ,i: 700 ,Loss_D: 0.47487372159957886 ,Loss_G: 3.1117334365844727 ,D(x): 0.7723142504692078 ,D(G(z)) 0.016015027156758063\n",
      "epoch: 54 ,i: 750 ,Loss_D: 0.02867407724261284 ,Loss_G: 6.623963356018066 ,D(x): 0.980455756187439 ,D(G(z)) 1.6123749519405544\n",
      "epoch: 55 ,i: 0 ,Loss_D: 0.13391931354999542 ,Loss_G: 4.490901947021484 ,D(x): 0.9427578449249268 ,D(G(z)) 2.012128959164699\n",
      "epoch: 55 ,i: 50 ,Loss_D: 0.13846446573734283 ,Loss_G: 3.6052334308624268 ,D(x): 0.8988282680511475 ,D(G(z)) 0.13197119716944883\n",
      "epoch: 55 ,i: 100 ,Loss_D: 0.04885092377662659 ,Loss_G: 6.596319198608398 ,D(x): 0.9952369332313538 ,D(G(z)) 9.028941464266099\n",
      "epoch: 55 ,i: 150 ,Loss_D: 0.040287647396326065 ,Loss_G: 5.968446254730225 ,D(x): 0.9663522243499756 ,D(G(z)) 0.6301485829402508\n",
      "epoch: 55 ,i: 200 ,Loss_D: 0.021191179752349854 ,Loss_G: 7.259139537811279 ,D(x): 0.9856566786766052 ,D(G(z)) 2.276857120723835\n",
      "epoch: 55 ,i: 250 ,Loss_D: 0.034396976232528687 ,Loss_G: 7.459212303161621 ,D(x): 0.9726431369781494 ,D(G(z)) 1.5802398516194651\n",
      "epoch: 55 ,i: 300 ,Loss_D: 0.03044969215989113 ,Loss_G: 6.719939708709717 ,D(x): 0.997233510017395 ,D(G(z)) 6.527477708869208\n",
      "epoch: 55 ,i: 350 ,Loss_D: 0.026870835572481155 ,Loss_G: 6.959289073944092 ,D(x): 0.9865708947181702 ,D(G(z)) 3.943934194613515\n",
      "epoch: 55 ,i: 400 ,Loss_D: 0.030564703047275543 ,Loss_G: 6.163212776184082 ,D(x): 0.9809474945068359 ,D(G(z)) 1.586885489686813\n",
      "epoch: 55 ,i: 450 ,Loss_D: 0.19229567050933838 ,Loss_G: 5.716186046600342 ,D(x): 0.9699546694755554 ,D(G(z)) 13.737814291383954\n",
      "epoch: 55 ,i: 500 ,Loss_D: 0.09499628841876984 ,Loss_G: 6.190873146057129 ,D(x): 0.9426901936531067 ,D(G(z)) 3.058646936421779\n",
      "epoch: 55 ,i: 550 ,Loss_D: 0.041663091629743576 ,Loss_G: 6.4953765869140625 ,D(x): 0.9716653823852539 ,D(G(z)) 1.810914169869056\n",
      "epoch: 55 ,i: 600 ,Loss_D: 0.0444306880235672 ,Loss_G: 5.370365142822266 ,D(x): 0.9662407636642456 ,D(G(z)) 0.5562989145517439\n",
      "epoch: 55 ,i: 650 ,Loss_D: 0.061937518417835236 ,Loss_G: 5.439505577087402 ,D(x): 0.9801318049430847 ,D(G(z)) 3.701079113878279\n",
      "epoch: 55 ,i: 700 ,Loss_D: 0.061191946268081665 ,Loss_G: 5.231696128845215 ,D(x): 0.9703962802886963 ,D(G(z)) 1.7001440407286408\n",
      "epoch: 55 ,i: 750 ,Loss_D: 0.027152568101882935 ,Loss_G: 7.295231819152832 ,D(x): 0.9793657064437866 ,D(G(z)) 1.4458950572869902\n",
      "epoch: 56 ,i: 0 ,Loss_D: 0.432354599237442 ,Loss_G: 14.90781021118164 ,D(x): 0.9997897148132324 ,D(G(z)) 363478.8493597287\n",
      "epoch: 56 ,i: 50 ,Loss_D: 0.1510072499513626 ,Loss_G: 6.168551445007324 ,D(x): 0.8967697024345398 ,D(G(z)) 1.1823978405137472\n",
      "epoch: 56 ,i: 100 ,Loss_D: 0.02857530117034912 ,Loss_G: 7.677490234375 ,D(x): 0.986681342124939 ,D(G(z)) 8.57491032243035\n",
      "epoch: 56 ,i: 150 ,Loss_D: 0.10920330882072449 ,Loss_G: 4.058797836303711 ,D(x): 0.9183275103569031 ,D(G(z)) 0.18588042379003702\n",
      "epoch: 56 ,i: 200 ,Loss_D: 0.011325332336127758 ,Loss_G: 6.628626823425293 ,D(x): 0.9922600388526917 ,D(G(z)) 1.107419656672063\n",
      "epoch: 56 ,i: 250 ,Loss_D: 0.5708822011947632 ,Loss_G: 8.96129322052002 ,D(x): 0.995725154876709 ,D(G(z)) 569.1495829711934\n",
      "epoch: 56 ,i: 300 ,Loss_D: 1.4102567434310913 ,Loss_G: 13.47205638885498 ,D(x): 0.9988018870353699 ,D(G(z)) 71276.67284447813\n",
      "epoch: 56 ,i: 350 ,Loss_D: 1.3935009241104126 ,Loss_G: 18.052072525024414 ,D(x): 0.9999583959579468 ,D(G(z)) 9993510.585790358\n",
      "epoch: 56 ,i: 400 ,Loss_D: 0.026515424251556396 ,Loss_G: 6.645515441894531 ,D(x): 0.9884546399116516 ,D(G(z)) 3.1063254262964852\n",
      "epoch: 56 ,i: 450 ,Loss_D: 0.5768788456916809 ,Loss_G: 1.2928831577301025 ,D(x): 0.6877145171165466 ,D(G(z)) 0.004823873073780348\n",
      "epoch: 56 ,i: 500 ,Loss_D: 0.02733638323843479 ,Loss_G: 6.37123966217041 ,D(x): 0.9813865423202515 ,D(G(z)) 1.4911460784703543\n",
      "epoch: 56 ,i: 550 ,Loss_D: 0.023215416818857193 ,Loss_G: 7.298994064331055 ,D(x): 0.9873543977737427 ,D(G(z)) 2.825489230967034\n",
      "epoch: 56 ,i: 600 ,Loss_D: 0.03956441953778267 ,Loss_G: 5.686535835266113 ,D(x): 0.9933596849441528 ,D(G(z)) 3.083672308711874\n",
      "epoch: 56 ,i: 650 ,Loss_D: 0.047129176557064056 ,Loss_G: 5.941423416137695 ,D(x): 0.9883450269699097 ,D(G(z)) 3.12446543068741\n",
      "epoch: 56 ,i: 700 ,Loss_D: 0.14188706874847412 ,Loss_G: 7.376217842102051 ,D(x): 0.9993741512298584 ,D(G(z)) 64.37792097494895\n",
      "epoch: 56 ,i: 750 ,Loss_D: 0.0946199968457222 ,Loss_G: 3.7531118392944336 ,D(x): 0.9323740601539612 ,D(G(z)) 0.13151722677168706\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 57 ,i: 0 ,Loss_D: 5.0737810134887695 ,Loss_G: 20.935508728027344 ,D(x): 0.9999974370002747 ,D(G(z)) 98311836.17117518\n",
      "epoch: 57 ,i: 50 ,Loss_D: 0.07953749597072601 ,Loss_G: 5.619743824005127 ,D(x): 0.9661466479301453 ,D(G(z)) 3.321284337919081\n",
      "epoch: 57 ,i: 100 ,Loss_D: 0.06135331094264984 ,Loss_G: 7.1770219802856445 ,D(x): 0.9958125352859497 ,D(G(z)) 19.71116411773352\n",
      "epoch: 57 ,i: 150 ,Loss_D: 0.030988462269306183 ,Loss_G: 6.507450103759766 ,D(x): 0.9756956100463867 ,D(G(z)) 1.0831500415740225\n",
      "epoch: 57 ,i: 200 ,Loss_D: 0.10245542228221893 ,Loss_G: 7.695004463195801 ,D(x): 0.981945276260376 ,D(G(z)) 44.57939356215283\n",
      "epoch: 57 ,i: 250 ,Loss_D: 0.336934894323349 ,Loss_G: 3.0360655784606934 ,D(x): 0.7740802764892578 ,D(G(z)) 0.006577752504033789\n",
      "epoch: 57 ,i: 300 ,Loss_D: 0.043321967124938965 ,Loss_G: 6.674797058105469 ,D(x): 0.9947082996368408 ,D(G(z)) 10.568510642271864\n",
      "epoch: 57 ,i: 350 ,Loss_D: 0.16198492050170898 ,Loss_G: 7.6149163246154785 ,D(x): 0.9988301992416382 ,D(G(z)) 93.73591162775168\n",
      "epoch: 57 ,i: 400 ,Loss_D: 0.2961219847202301 ,Loss_G: 7.48819637298584 ,D(x): 0.7939518690109253 ,D(G(z)) 0.06937850754857754\n",
      "epoch: 57 ,i: 450 ,Loss_D: 0.06321486085653305 ,Loss_G: 5.7960615158081055 ,D(x): 0.99092698097229 ,D(G(z)) 5.518347281319103\n",
      "epoch: 57 ,i: 500 ,Loss_D: 0.038628950715065 ,Loss_G: 7.558006286621094 ,D(x): 0.9861330389976501 ,D(G(z)) 9.250788252012157\n",
      "epoch: 57 ,i: 550 ,Loss_D: 0.020790712907910347 ,Loss_G: 6.658658981323242 ,D(x): 0.9935241937637329 ,D(G(z)) 2.7592285566406747\n",
      "epoch: 57 ,i: 600 ,Loss_D: 0.03797132521867752 ,Loss_G: 6.969135284423828 ,D(x): 0.9922234416007996 ,D(G(z)) 12.953867727713417\n",
      "epoch: 57 ,i: 650 ,Loss_D: 0.0062230248004198074 ,Loss_G: 7.388400077819824 ,D(x): 0.996425986289978 ,D(G(z)) 0.9745972170411942\n",
      "epoch: 57 ,i: 700 ,Loss_D: 0.2513316869735718 ,Loss_G: 5.774667263031006 ,D(x): 0.9723851084709167 ,D(G(z)) 30.49511411846143\n",
      "epoch: 57 ,i: 750 ,Loss_D: 0.018820468336343765 ,Loss_G: 5.936458587646484 ,D(x): 0.9977658987045288 ,D(G(z)) 2.634866362025212\n",
      "epoch: 58 ,i: 0 ,Loss_D: 0.5853514671325684 ,Loss_G: 14.919696807861328 ,D(x): 0.9998525977134705 ,D(G(z)) 85580.27506849456\n",
      "epoch: 58 ,i: 50 ,Loss_D: 0.1732887327671051 ,Loss_G: 6.401424407958984 ,D(x): 0.8809128999710083 ,D(G(z)) 0.30239131582821305\n",
      "epoch: 58 ,i: 100 ,Loss_D: 0.030222401022911072 ,Loss_G: 6.3120856285095215 ,D(x): 0.9828993082046509 ,D(G(z)) 1.3967995574379757\n",
      "epoch: 58 ,i: 150 ,Loss_D: 0.3291471302509308 ,Loss_G: 6.1600823402404785 ,D(x): 0.918302059173584 ,D(G(z)) 42.6656809253845\n",
      "epoch: 58 ,i: 200 ,Loss_D: 0.035210974514484406 ,Loss_G: 6.521966457366943 ,D(x): 0.9830705523490906 ,D(G(z)) 1.7681672719353125\n",
      "epoch: 58 ,i: 250 ,Loss_D: 0.0293694119900465 ,Loss_G: 5.765758514404297 ,D(x): 0.9840570688247681 ,D(G(z)) 1.358593259910879\n",
      "epoch: 58 ,i: 300 ,Loss_D: 0.03310033306479454 ,Loss_G: 6.4571356773376465 ,D(x): 0.982286810874939 ,D(G(z)) 2.0451635205201932\n",
      "epoch: 58 ,i: 350 ,Loss_D: 0.09057319909334183 ,Loss_G: 4.8703155517578125 ,D(x): 0.9227076768875122 ,D(G(z)) 0.15141388396599287\n",
      "epoch: 58 ,i: 400 ,Loss_D: 0.029248137027025223 ,Loss_G: 6.655801773071289 ,D(x): 0.994211733341217 ,D(G(z)) 5.633645571329246\n",
      "epoch: 58 ,i: 450 ,Loss_D: 0.027231507003307343 ,Loss_G: 6.114815711975098 ,D(x): 0.984412670135498 ,D(G(z)) 2.3280547819197235\n",
      "epoch: 58 ,i: 500 ,Loss_D: 0.014977069571614265 ,Loss_G: 8.823436737060547 ,D(x): 0.9865243434906006 ,D(G(z)) 1.053872328078639\n",
      "epoch: 58 ,i: 550 ,Loss_D: 0.0447247251868248 ,Loss_G: 7.254560947418213 ,D(x): 0.9959660768508911 ,D(G(z)) 19.001557013938548\n",
      "epoch: 58 ,i: 600 ,Loss_D: 0.021682025864720345 ,Loss_G: 5.60042667388916 ,D(x): 0.9921423196792603 ,D(G(z)) 1.044051161783296\n",
      "epoch: 58 ,i: 650 ,Loss_D: 3.550191640853882 ,Loss_G: 10.931190490722656 ,D(x): 0.9450808763504028 ,D(G(z)) 5018.580522901909\n",
      "epoch: 58 ,i: 700 ,Loss_D: 0.10507847368717194 ,Loss_G: 5.475672721862793 ,D(x): 0.9773508310317993 ,D(G(z)) 6.057747176365786\n",
      "epoch: 58 ,i: 750 ,Loss_D: 0.0491911843419075 ,Loss_G: 6.669318199157715 ,D(x): 0.9938160181045532 ,D(G(z)) 14.659110094861576\n",
      "epoch: 59 ,i: 0 ,Loss_D: 2.6370410919189453 ,Loss_G: 21.460365295410156 ,D(x): 0.9999984502792358 ,D(G(z)) 153521372.6178379\n",
      "epoch: 59 ,i: 50 ,Loss_D: 0.053203582763671875 ,Loss_G: 6.511636734008789 ,D(x): 0.9797296524047852 ,D(G(z)) 6.004225580607817\n",
      "epoch: 59 ,i: 100 ,Loss_D: 3.181804895401001 ,Loss_G: 0.8284147381782532 ,D(x): 0.13979099690914154 ,D(G(z)) 0.0010343697785561079\n",
      "epoch: 59 ,i: 150 ,Loss_D: 0.11419375985860825 ,Loss_G: 4.483131408691406 ,D(x): 0.9652424454689026 ,D(G(z)) 1.9419102424776802\n",
      "epoch: 59 ,i: 200 ,Loss_D: 0.06715895980596542 ,Loss_G: 7.055391788482666 ,D(x): 0.9970362186431885 ,D(G(z)) 19.67132129420483\n",
      "epoch: 59 ,i: 250 ,Loss_D: 0.3400978744029999 ,Loss_G: 6.206038951873779 ,D(x): 0.9306212663650513 ,D(G(z)) 22.746269835939938\n",
      "epoch: 59 ,i: 300 ,Loss_D: 0.10195978730916977 ,Loss_G: 5.045467376708984 ,D(x): 0.9381746053695679 ,D(G(z)) 0.9632199467507356\n",
      "epoch: 59 ,i: 350 ,Loss_D: 0.07829156517982483 ,Loss_G: 7.342411994934082 ,D(x): 0.9802606105804443 ,D(G(z)) 11.96793711439552\n",
      "epoch: 59 ,i: 400 ,Loss_D: 0.03265853598713875 ,Loss_G: 5.560929298400879 ,D(x): 0.9818940162658691 ,D(G(z)) 1.163973209615719\n",
      "epoch: 59 ,i: 450 ,Loss_D: 0.09123657643795013 ,Loss_G: 5.5983123779296875 ,D(x): 0.9881877899169922 ,D(G(z)) 8.93546208366517\n",
      "epoch: 59 ,i: 500 ,Loss_D: 0.025353804230690002 ,Loss_G: 6.77685022354126 ,D(x): 0.9928365349769592 ,D(G(z)) 3.536246466333534\n",
      "epoch: 59 ,i: 550 ,Loss_D: 0.08171425759792328 ,Loss_G: 4.642447471618652 ,D(x): 0.9505323767662048 ,D(G(z)) 1.0390359084536709\n",
      "epoch: 59 ,i: 600 ,Loss_D: 0.032735586166381836 ,Loss_G: 6.263614654541016 ,D(x): 0.9957617521286011 ,D(G(z)) 3.494775322529613\n",
      "epoch: 59 ,i: 650 ,Loss_D: 0.3965470492839813 ,Loss_G: 3.157405376434326 ,D(x): 0.8564105033874512 ,D(G(z)) 1.5369116912593688\n",
      "epoch: 59 ,i: 700 ,Loss_D: 0.15783703327178955 ,Loss_G: 6.746214866638184 ,D(x): 0.982111394405365 ,D(G(z)) 22.22913069890722\n",
      "epoch: 59 ,i: 750 ,Loss_D: 0.04230393469333649 ,Loss_G: 5.52364444732666 ,D(x): 0.9715703129768372 ,D(G(z)) 0.9004231638887875\n",
      "epoch: 60 ,i: 0 ,Loss_D: 1.3983649015426636 ,Loss_G: 8.29737663269043 ,D(x): 0.9652179479598999 ,D(G(z)) 455.794830201826\n",
      "epoch: 60 ,i: 50 ,Loss_D: 0.11845149844884872 ,Loss_G: 5.278571605682373 ,D(x): 0.9391460418701172 ,D(G(z)) 1.7109988028961032\n",
      "epoch: 60 ,i: 100 ,Loss_D: 0.07831236720085144 ,Loss_G: 5.742298603057861 ,D(x): 0.9693781733512878 ,D(G(z)) 2.0483192325706683\n",
      "epoch: 60 ,i: 150 ,Loss_D: 0.04672955349087715 ,Loss_G: 5.961029529571533 ,D(x): 0.9707428216934204 ,D(G(z)) 0.41275417279230325\n",
      "epoch: 60 ,i: 200 ,Loss_D: 0.0646611824631691 ,Loss_G: 6.100429534912109 ,D(x): 0.9940541982650757 ,D(G(z)) 9.557166891579582\n",
      "epoch: 60 ,i: 250 ,Loss_D: 0.16795507073402405 ,Loss_G: 3.3746073246002197 ,D(x): 0.8693781495094299 ,D(G(z)) 0.028099532222972703\n",
      "epoch: 60 ,i: 300 ,Loss_D: 0.08405005931854248 ,Loss_G: 5.223579406738281 ,D(x): 0.9311221241950989 ,D(G(z)) 0.28811439414893675\n",
      "epoch: 60 ,i: 350 ,Loss_D: 0.08031357824802399 ,Loss_G: 6.750827312469482 ,D(x): 0.9782308340072632 ,D(G(z)) 9.955712772724432\n",
      "epoch: 60 ,i: 400 ,Loss_D: 0.0127528365701437 ,Loss_G: 6.1574530601501465 ,D(x): 0.9927359819412231 ,D(G(z)) 0.6158743408368682\n",
      "epoch: 60 ,i: 450 ,Loss_D: 0.33094388246536255 ,Loss_G: 5.047807216644287 ,D(x): 0.939104437828064 ,D(G(z)) 12.12235394352274\n",
      "epoch: 60 ,i: 500 ,Loss_D: 0.3243383765220642 ,Loss_G: 5.515623092651367 ,D(x): 0.9822496175765991 ,D(G(z)) 17.750519403031486\n",
      "epoch: 60 ,i: 550 ,Loss_D: 0.06006832793354988 ,Loss_G: 7.304083824157715 ,D(x): 0.9950376749038696 ,D(G(z)) 13.797968631958211\n",
      "epoch: 60 ,i: 600 ,Loss_D: 0.06004125997424126 ,Loss_G: 7.020004749298096 ,D(x): 0.9959045052528381 ,D(G(z)) 22.592609386384783\n",
      "epoch: 60 ,i: 650 ,Loss_D: 0.08412706851959229 ,Loss_G: 6.593100547790527 ,D(x): 0.992779552936554 ,D(G(z)) 11.587093223496762\n",
      "epoch: 60 ,i: 700 ,Loss_D: 3.1662845611572266 ,Loss_G: 12.249353408813477 ,D(x): 0.9996994137763977 ,D(G(z)) 32380.667894673286\n",
      "epoch: 60 ,i: 750 ,Loss_D: 0.08433029055595398 ,Loss_G: 5.064599990844727 ,D(x): 0.9341815710067749 ,D(G(z)) 0.1157199543099765\n",
      "epoch: 61 ,i: 0 ,Loss_D: 0.01684870570898056 ,Loss_G: 6.654419898986816 ,D(x): 0.9905713200569153 ,D(G(z)) 1.3019461673483343\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 61 ,i: 50 ,Loss_D: 0.02785426750779152 ,Loss_G: 6.454148292541504 ,D(x): 0.9821670651435852 ,D(G(z)) 1.5386756930797465\n",
      "epoch: 61 ,i: 100 ,Loss_D: 0.021142862737178802 ,Loss_G: 6.015195846557617 ,D(x): 0.9927397966384888 ,D(G(z)) 2.0339656523275162\n",
      "epoch: 61 ,i: 150 ,Loss_D: 0.020670417696237564 ,Loss_G: 5.069217205047607 ,D(x): 0.9928778409957886 ,D(G(z)) 0.8202790302126282\n",
      "epoch: 61 ,i: 200 ,Loss_D: 0.07004514336585999 ,Loss_G: 5.4617838859558105 ,D(x): 0.9515713453292847 ,D(G(z)) 0.9538666737964535\n",
      "epoch: 61 ,i: 250 ,Loss_D: 0.1402432769536972 ,Loss_G: 2.8453121185302734 ,D(x): 0.8985885381698608 ,D(G(z)) 0.17627270445304652\n",
      "epoch: 61 ,i: 300 ,Loss_D: 0.06917133927345276 ,Loss_G: 6.914978504180908 ,D(x): 0.9707969427108765 ,D(G(z)) 4.730181127469798\n",
      "epoch: 61 ,i: 350 ,Loss_D: 0.017540810629725456 ,Loss_G: 6.625515937805176 ,D(x): 0.9939839839935303 ,D(G(z)) 2.185975449795597\n",
      "epoch: 61 ,i: 400 ,Loss_D: 0.07964111864566803 ,Loss_G: 4.838715553283691 ,D(x): 0.9466414451599121 ,D(G(z)) 0.5350113617315913\n",
      "epoch: 61 ,i: 450 ,Loss_D: 0.06743350625038147 ,Loss_G: 6.778243064880371 ,D(x): 0.969378650188446 ,D(G(z)) 4.561120196551997\n",
      "epoch: 61 ,i: 500 ,Loss_D: 0.07335661351680756 ,Loss_G: 4.586993217468262 ,D(x): 0.9520232081413269 ,D(G(z)) 0.6657244987923556\n",
      "epoch: 61 ,i: 550 ,Loss_D: 0.02027948573231697 ,Loss_G: 6.7076005935668945 ,D(x): 0.9928163886070251 ,D(G(z)) 3.1849488914267488\n",
      "epoch: 61 ,i: 600 ,Loss_D: 0.0664757564663887 ,Loss_G: 5.086605072021484 ,D(x): 0.9732779264450073 ,D(G(z)) 1.991482586175046\n",
      "epoch: 61 ,i: 650 ,Loss_D: 0.02766350656747818 ,Loss_G: 5.941048622131348 ,D(x): 0.9891775846481323 ,D(G(z)) 1.846403001143897\n",
      "epoch: 61 ,i: 700 ,Loss_D: 0.12469097971916199 ,Loss_G: 7.949071884155273 ,D(x): 0.8956218957901001 ,D(G(z)) 0.2213287967060979\n",
      "epoch: 61 ,i: 750 ,Loss_D: 0.08102811872959137 ,Loss_G: 6.123298645019531 ,D(x): 0.9575231075286865 ,D(G(z)) 1.09677700994973\n",
      "epoch: 62 ,i: 0 ,Loss_D: 0.0757012665271759 ,Loss_G: 5.723899841308594 ,D(x): 0.9981350898742676 ,D(G(z)) 7.015562805732512\n",
      "epoch: 62 ,i: 50 ,Loss_D: 0.037484411150217056 ,Loss_G: 5.5538530349731445 ,D(x): 0.9988890886306763 ,D(G(z)) 4.748068879052052\n",
      "epoch: 62 ,i: 100 ,Loss_D: 0.026936328038573265 ,Loss_G: 6.5543694496154785 ,D(x): 0.9818225502967834 ,D(G(z)) 1.6774990139144503\n",
      "epoch: 62 ,i: 150 ,Loss_D: 0.048766881227493286 ,Loss_G: 6.685809135437012 ,D(x): 0.997209906578064 ,D(G(z)) 14.18942158208637\n",
      "epoch: 62 ,i: 200 ,Loss_D: 0.01831543818116188 ,Loss_G: 6.431602478027344 ,D(x): 0.9883977174758911 ,D(G(z)) 1.0091326403618155\n",
      "epoch: 62 ,i: 250 ,Loss_D: 0.027948834002017975 ,Loss_G: 6.506550312042236 ,D(x): 0.9765530824661255 ,D(G(z)) 0.3116798600549738\n",
      "epoch: 62 ,i: 300 ,Loss_D: 0.01316651701927185 ,Loss_G: 7.235732078552246 ,D(x): 0.993653416633606 ,D(G(z)) 2.3190520333063187\n",
      "epoch: 62 ,i: 350 ,Loss_D: 0.4841257929801941 ,Loss_G: 2.9217076301574707 ,D(x): 0.829299807548523 ,D(G(z)) 0.9713845714778782\n",
      "epoch: 62 ,i: 400 ,Loss_D: 0.053004756569862366 ,Loss_G: 7.628302574157715 ,D(x): 0.9932060241699219 ,D(G(z)) 28.994645746372296\n",
      "epoch: 62 ,i: 450 ,Loss_D: 0.03221184387803078 ,Loss_G: 6.711814880371094 ,D(x): 0.9858896136283875 ,D(G(z)) 3.5484001228847513\n",
      "epoch: 62 ,i: 500 ,Loss_D: 0.09613493084907532 ,Loss_G: 5.754232406616211 ,D(x): 0.9909812211990356 ,D(G(z)) 5.5371534069266675\n",
      "epoch: 62 ,i: 550 ,Loss_D: 0.13923344016075134 ,Loss_G: 3.8468165397644043 ,D(x): 0.9280173778533936 ,D(G(z)) 0.49501211863739253\n",
      "epoch: 62 ,i: 600 ,Loss_D: 0.7350355982780457 ,Loss_G: 3.152956008911133 ,D(x): 0.628156304359436 ,D(G(z)) 0.8900549847645213\n",
      "epoch: 62 ,i: 650 ,Loss_D: 0.476343035697937 ,Loss_G: 5.136037826538086 ,D(x): 0.9630920886993408 ,D(G(z)) 22.066706042605567\n",
      "epoch: 62 ,i: 700 ,Loss_D: 0.08384519815444946 ,Loss_G: 5.067797660827637 ,D(x): 0.9314367175102234 ,D(G(z)) 0.14612858006415233\n",
      "epoch: 62 ,i: 750 ,Loss_D: 0.48591727018356323 ,Loss_G: 3.5813629627227783 ,D(x): 0.9808559417724609 ,D(G(z)) 5.149548022443547\n",
      "epoch: 63 ,i: 0 ,Loss_D: 0.06374441087245941 ,Loss_G: 5.705381393432617 ,D(x): 0.9720331430435181 ,D(G(z)) 3.592908820632653\n",
      "epoch: 63 ,i: 50 ,Loss_D: 0.022612575441598892 ,Loss_G: 8.688613891601562 ,D(x): 0.9832547307014465 ,D(G(z)) 5.103277796675072\n",
      "epoch: 63 ,i: 100 ,Loss_D: 1.4335007667541504 ,Loss_G: 1.6448287963867188 ,D(x): 0.35774803161621094 ,D(G(z)) 0.04771101894370514\n",
      "epoch: 63 ,i: 150 ,Loss_D: 0.04106874018907547 ,Loss_G: 5.7618489265441895 ,D(x): 0.9903954267501831 ,D(G(z)) 3.433137059740028\n",
      "epoch: 63 ,i: 200 ,Loss_D: 0.07768377661705017 ,Loss_G: 6.839594841003418 ,D(x): 0.9912456274032593 ,D(G(z)) 14.372146324669536\n",
      "epoch: 63 ,i: 250 ,Loss_D: 0.08740083128213882 ,Loss_G: 6.821800708770752 ,D(x): 0.9299948215484619 ,D(G(z)) 1.8340051678669416\n",
      "epoch: 63 ,i: 300 ,Loss_D: 0.03863842040300369 ,Loss_G: 5.608321666717529 ,D(x): 0.9891365766525269 ,D(G(z)) 2.6185313743687026\n",
      "epoch: 63 ,i: 350 ,Loss_D: 0.028143260627985 ,Loss_G: 6.025472164154053 ,D(x): 0.9944756627082825 ,D(G(z)) 2.70096857052925\n",
      "epoch: 63 ,i: 400 ,Loss_D: 0.02500026859343052 ,Loss_G: 9.292953491210938 ,D(x): 0.976447582244873 ,D(G(z)) 1.0858720447312236\n",
      "epoch: 63 ,i: 450 ,Loss_D: 0.09191986918449402 ,Loss_G: 4.320082664489746 ,D(x): 0.9322960376739502 ,D(G(z)) 0.2513304942928078\n",
      "epoch: 63 ,i: 500 ,Loss_D: 0.049440301954746246 ,Loss_G: 4.9662251472473145 ,D(x): 0.9687973260879517 ,D(G(z)) 0.8101011606946444\n",
      "epoch: 63 ,i: 550 ,Loss_D: 0.04631701484322548 ,Loss_G: 5.541681289672852 ,D(x): 0.9925713539123535 ,D(G(z)) 3.275851969535906\n",
      "epoch: 63 ,i: 600 ,Loss_D: 0.02597079798579216 ,Loss_G: 6.028766632080078 ,D(x): 0.9944632053375244 ,D(G(z)) 3.2672824216502288\n",
      "epoch: 63 ,i: 650 ,Loss_D: 0.021796587854623795 ,Loss_G: 6.528133392333984 ,D(x): 0.9951989650726318 ,D(G(z)) 3.4234016475753126\n",
      "epoch: 63 ,i: 700 ,Loss_D: 0.29162776470184326 ,Loss_G: 3.129687786102295 ,D(x): 0.9049820899963379 ,D(G(z)) 1.464269460806138\n",
      "epoch: 63 ,i: 750 ,Loss_D: 0.1459672898054123 ,Loss_G: 6.085406303405762 ,D(x): 0.9972104430198669 ,D(G(z)) 15.750504712128803\n",
      "epoch: 64 ,i: 0 ,Loss_D: 0.10649100691080093 ,Loss_G: 7.188479900360107 ,D(x): 0.9935649037361145 ,D(G(z)) 35.68319857148107\n",
      "epoch: 64 ,i: 50 ,Loss_D: 0.03714440390467644 ,Loss_G: 6.126770973205566 ,D(x): 0.9977039098739624 ,D(G(z)) 3.8986266812949433\n",
      "epoch: 64 ,i: 100 ,Loss_D: 0.06361563503742218 ,Loss_G: 4.148448944091797 ,D(x): 0.9543925523757935 ,D(G(z)) 0.36373468724948604\n",
      "epoch: 64 ,i: 150 ,Loss_D: 0.18030741810798645 ,Loss_G: 4.014003276824951 ,D(x): 0.879311740398407 ,D(G(z)) 0.24432963004796066\n",
      "epoch: 64 ,i: 200 ,Loss_D: 0.0675603374838829 ,Loss_G: 5.456789970397949 ,D(x): 0.9462265968322754 ,D(G(z)) 0.3837516582162767\n",
      "epoch: 64 ,i: 250 ,Loss_D: 0.4739885926246643 ,Loss_G: 2.0756351947784424 ,D(x): 0.9629092812538147 ,D(G(z)) 1.6768036800925286\n",
      "epoch: 64 ,i: 300 ,Loss_D: 0.06087354198098183 ,Loss_G: 5.172492027282715 ,D(x): 0.9672490358352661 ,D(G(z)) 1.1448567134916496\n",
      "epoch: 64 ,i: 350 ,Loss_D: 0.04258754849433899 ,Loss_G: 5.531674385070801 ,D(x): 0.9737164974212646 ,D(G(z)) 1.3397237955391523\n",
      "epoch: 64 ,i: 400 ,Loss_D: 0.057204317301511765 ,Loss_G: 6.474737167358398 ,D(x): 0.9916553497314453 ,D(G(z)) 10.682687460102994\n",
      "epoch: 64 ,i: 450 ,Loss_D: 0.06662401556968689 ,Loss_G: 5.463219165802002 ,D(x): 0.9673698544502258 ,D(G(z)) 2.357379983033186\n",
      "epoch: 64 ,i: 500 ,Loss_D: 0.029811738058924675 ,Loss_G: 5.638854026794434 ,D(x): 0.9892493486404419 ,D(G(z)) 2.057256460112947\n",
      "epoch: 64 ,i: 550 ,Loss_D: 0.051228925585746765 ,Loss_G: 6.682417869567871 ,D(x): 0.9704999923706055 ,D(G(z)) 2.599557095567254\n",
      "epoch: 64 ,i: 600 ,Loss_D: 0.012737673707306385 ,Loss_G: 5.971702575683594 ,D(x): 0.9961833357810974 ,D(G(z)) 1.2292960598808638\n",
      "epoch: 64 ,i: 650 ,Loss_D: 0.018647070974111557 ,Loss_G: 7.90606164932251 ,D(x): 0.9908410310745239 ,D(G(z)) 8.027429263140771\n",
      "epoch: 64 ,i: 700 ,Loss_D: 0.012530171312391758 ,Loss_G: 5.444299697875977 ,D(x): 0.9984478950500488 ,D(G(z)) 0.8807558302214532\n",
      "epoch: 64 ,i: 750 ,Loss_D: 0.05215613171458244 ,Loss_G: 6.929130554199219 ,D(x): 0.9514419436454773 ,D(G(z)) 0.2684601203182612\n",
      "epoch: 65 ,i: 0 ,Loss_D: 0.025931397452950478 ,Loss_G: 5.316069602966309 ,D(x): 0.9939342737197876 ,D(G(z)) 1.3472492111589522\n",
      "epoch: 65 ,i: 50 ,Loss_D: 0.19490422308444977 ,Loss_G: 11.476192474365234 ,D(x): 0.999339759349823 ,D(G(z)) 5123.784074210954\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 65 ,i: 100 ,Loss_D: 0.019931582733988762 ,Loss_G: 6.259254455566406 ,D(x): 0.9959501028060913 ,D(G(z)) 2.4255934511222415\n",
      "epoch: 65 ,i: 150 ,Loss_D: 0.03582017868757248 ,Loss_G: 6.7697553634643555 ,D(x): 0.9889664649963379 ,D(G(z)) 5.3485169989133015\n",
      "epoch: 65 ,i: 200 ,Loss_D: 5.562068462371826 ,Loss_G: 1.0974522829055786 ,D(x): 0.018443550914525986 ,D(G(z)) 0.000129006739881456\n",
      "epoch: 65 ,i: 250 ,Loss_D: 0.046735234558582306 ,Loss_G: 7.573892116546631 ,D(x): 0.9754616022109985 ,D(G(z)) 5.5267966442326495\n",
      "epoch: 65 ,i: 300 ,Loss_D: 1.1445156335830688 ,Loss_G: 8.036365509033203 ,D(x): 0.9895235300064087 ,D(G(z)) 452.6856059482108\n",
      "epoch: 65 ,i: 350 ,Loss_D: 0.4576352834701538 ,Loss_G: 6.262932777404785 ,D(x): 0.982164740562439 ,D(G(z)) 47.70649834131173\n",
      "epoch: 65 ,i: 400 ,Loss_D: 0.07355767488479614 ,Loss_G: 6.869049072265625 ,D(x): 0.9902467727661133 ,D(G(z)) 12.407488127759054\n",
      "epoch: 65 ,i: 450 ,Loss_D: 0.14800448715686798 ,Loss_G: 7.6912078857421875 ,D(x): 0.9980407953262329 ,D(G(z)) 108.5769429281384\n",
      "epoch: 65 ,i: 500 ,Loss_D: 0.1239490658044815 ,Loss_G: 5.099661827087402 ,D(x): 0.9010872840881348 ,D(G(z)) 0.0841881259781707\n",
      "epoch: 65 ,i: 550 ,Loss_D: 0.23450914025306702 ,Loss_G: 2.3540968894958496 ,D(x): 0.8211700916290283 ,D(G(z)) 0.009870640118930917\n",
      "epoch: 65 ,i: 600 ,Loss_D: 0.24417877197265625 ,Loss_G: 7.962080001831055 ,D(x): 0.9954092502593994 ,D(G(z)) 159.58912151238223\n",
      "epoch: 65 ,i: 650 ,Loss_D: 0.10651946067810059 ,Loss_G: 6.0481367111206055 ,D(x): 0.922840416431427 ,D(G(z)) 1.3852211797014347\n",
      "epoch: 65 ,i: 700 ,Loss_D: 0.06783060729503632 ,Loss_G: 4.893951892852783 ,D(x): 0.9685640335083008 ,D(G(z)) 1.4067434179295577\n",
      "epoch: 65 ,i: 750 ,Loss_D: 0.06758332997560501 ,Loss_G: 6.184370040893555 ,D(x): 0.9879412651062012 ,D(G(z)) 6.948735241291809\n",
      "epoch: 66 ,i: 0 ,Loss_D: 0.25101420283317566 ,Loss_G: 10.331121444702148 ,D(x): 0.994446873664856 ,D(G(z)) 1437.4745503625136\n",
      "epoch: 66 ,i: 50 ,Loss_D: 0.03753616660833359 ,Loss_G: 6.730913162231445 ,D(x): 0.9943304061889648 ,D(G(z)) 7.959216489100879\n",
      "epoch: 66 ,i: 100 ,Loss_D: 0.028608186170458794 ,Loss_G: 6.382931709289551 ,D(x): 0.9969373345375061 ,D(G(z)) 4.557545511289778\n",
      "epoch: 66 ,i: 150 ,Loss_D: 0.01974288746714592 ,Loss_G: 6.268894195556641 ,D(x): 0.9968678951263428 ,D(G(z)) 3.238798483260951\n",
      "epoch: 66 ,i: 200 ,Loss_D: 0.011571214534342289 ,Loss_G: 6.716148853302002 ,D(x): 0.9937112927436829 ,D(G(z)) 1.513219805168631\n",
      "epoch: 66 ,i: 250 ,Loss_D: 0.43666553497314453 ,Loss_G: 3.304917573928833 ,D(x): 0.7537683844566345 ,D(G(z)) 0.18434856511176725\n",
      "epoch: 66 ,i: 300 ,Loss_D: 0.04182567447423935 ,Loss_G: 6.692530632019043 ,D(x): 0.986677348613739 ,D(G(z)) 6.700889016068015\n",
      "epoch: 66 ,i: 350 ,Loss_D: 0.09398695081472397 ,Loss_G: 6.816556930541992 ,D(x): 0.9924262166023254 ,D(G(z)) 18.119427960956912\n",
      "epoch: 66 ,i: 400 ,Loss_D: 0.02075859159231186 ,Loss_G: 7.64155387878418 ,D(x): 0.9903963804244995 ,D(G(z)) 2.9590703311038467\n",
      "epoch: 66 ,i: 450 ,Loss_D: 0.050139717757701874 ,Loss_G: 6.046349048614502 ,D(x): 0.9614051580429077 ,D(G(z)) 0.6384425206106562\n",
      "epoch: 66 ,i: 500 ,Loss_D: 0.04143268242478371 ,Loss_G: 6.5158491134643555 ,D(x): 0.9865911602973938 ,D(G(z)) 4.190943346976578\n",
      "epoch: 66 ,i: 550 ,Loss_D: 0.017860764637589455 ,Loss_G: 5.900861740112305 ,D(x): 0.9958295822143555 ,D(G(z)) 1.8094889946429769\n",
      "epoch: 66 ,i: 600 ,Loss_D: 0.02366618998348713 ,Loss_G: 7.281644821166992 ,D(x): 0.9906758069992065 ,D(G(z)) 4.664998797512249\n",
      "epoch: 66 ,i: 650 ,Loss_D: 0.032144203782081604 ,Loss_G: 5.928866386413574 ,D(x): 0.9806379079818726 ,D(G(z)) 1.1663173013006058\n",
      "epoch: 66 ,i: 700 ,Loss_D: 0.017327146604657173 ,Loss_G: 6.48722505569458 ,D(x): 0.9994246959686279 ,D(G(z)) 2.303828183606325\n",
      "epoch: 66 ,i: 750 ,Loss_D: 0.23726865649223328 ,Loss_G: 6.053829669952393 ,D(x): 0.9755203723907471 ,D(G(z)) 27.584287878533775\n",
      "epoch: 67 ,i: 0 ,Loss_D: 0.09323534369468689 ,Loss_G: 5.8364081382751465 ,D(x): 0.9957212209701538 ,D(G(z)) 9.775878788186004\n",
      "epoch: 67 ,i: 50 ,Loss_D: 0.05162377655506134 ,Loss_G: 5.843567848205566 ,D(x): 0.9735963344573975 ,D(G(z)) 2.0958722467971618\n",
      "epoch: 67 ,i: 100 ,Loss_D: 0.3264608383178711 ,Loss_G: 5.572701454162598 ,D(x): 0.944421648979187 ,D(G(z)) 14.801298127752657\n",
      "epoch: 67 ,i: 150 ,Loss_D: 1.9179916381835938 ,Loss_G: 15.057933807373047 ,D(x): 0.9998630881309509 ,D(G(z)) 115627.89456731471\n",
      "epoch: 67 ,i: 200 ,Loss_D: 0.09533390402793884 ,Loss_G: 6.061321258544922 ,D(x): 0.9669649600982666 ,D(G(z)) 3.8676166068222333\n",
      "epoch: 67 ,i: 250 ,Loss_D: 0.04258636757731438 ,Loss_G: 7.143719673156738 ,D(x): 0.9953640699386597 ,D(G(z)) 15.201281626133216\n",
      "epoch: 67 ,i: 300 ,Loss_D: 0.12322641909122467 ,Loss_G: 7.008238315582275 ,D(x): 0.980782151222229 ,D(G(z)) 18.36040179826053\n",
      "epoch: 67 ,i: 350 ,Loss_D: 0.018343539908528328 ,Loss_G: 5.930347442626953 ,D(x): 0.9988009929656982 ,D(G(z)) 1.9453346893856687\n",
      "epoch: 67 ,i: 400 ,Loss_D: 0.09968370199203491 ,Loss_G: 4.176229953765869 ,D(x): 0.9180111289024353 ,D(G(z)) 0.14166864989398137\n",
      "epoch: 67 ,i: 450 ,Loss_D: 0.24555300176143646 ,Loss_G: 5.908349514007568 ,D(x): 0.9990395903587341 ,D(G(z)) 31.863194138533103\n",
      "epoch: 67 ,i: 500 ,Loss_D: 0.030709201470017433 ,Loss_G: 6.49931526184082 ,D(x): 0.9988357424736023 ,D(G(z)) 4.915653579752542\n",
      "epoch: 67 ,i: 550 ,Loss_D: 0.06905245780944824 ,Loss_G: 6.515823841094971 ,D(x): 0.9828086495399475 ,D(G(z)) 8.54661137457054\n",
      "epoch: 67 ,i: 600 ,Loss_D: 0.08320088684558868 ,Loss_G: 8.104549407958984 ,D(x): 0.997285008430481 ,D(G(z)) 54.48838222604025\n",
      "epoch: 67 ,i: 650 ,Loss_D: 0.025006646290421486 ,Loss_G: 6.8342108726501465 ,D(x): 0.9797197580337524 ,D(G(z)) 0.8832344272575001\n",
      "epoch: 67 ,i: 700 ,Loss_D: 0.025624625384807587 ,Loss_G: 7.258204460144043 ,D(x): 0.9768815040588379 ,D(G(z)) 0.8661614640490831\n",
      "epoch: 67 ,i: 750 ,Loss_D: 0.052373483777046204 ,Loss_G: 6.375589370727539 ,D(x): 0.975932240486145 ,D(G(z)) 3.2231491349048174\n",
      "epoch: 68 ,i: 0 ,Loss_D: 0.02684972807765007 ,Loss_G: 6.407872200012207 ,D(x): 0.9974911212921143 ,D(G(z)) 5.957132700589497\n",
      "epoch: 68 ,i: 50 ,Loss_D: 0.01951238140463829 ,Loss_G: 5.957464218139648 ,D(x): 0.9909969568252563 ,D(G(z)) 1.3943440516935308\n",
      "epoch: 68 ,i: 100 ,Loss_D: 0.022259308025240898 ,Loss_G: 6.451822280883789 ,D(x): 0.9895235300064087 ,D(G(z)) 2.689862050745706\n",
      "epoch: 68 ,i: 150 ,Loss_D: 0.404577374458313 ,Loss_G: 4.69632625579834 ,D(x): 0.7574517726898193 ,D(G(z)) 0.7905185745772778\n",
      "epoch: 68 ,i: 200 ,Loss_D: 0.0595141276717186 ,Loss_G: 6.086887359619141 ,D(x): 0.965097188949585 ,D(G(z)) 2.520854492053471\n",
      "epoch: 68 ,i: 250 ,Loss_D: 0.26401251554489136 ,Loss_G: 3.9975273609161377 ,D(x): 0.8747403025627136 ,D(G(z)) 1.7890976253854125\n",
      "epoch: 68 ,i: 300 ,Loss_D: 0.12951543927192688 ,Loss_G: 6.316839694976807 ,D(x): 0.9961084127426147 ,D(G(z)) 23.482124540439145\n",
      "epoch: 68 ,i: 350 ,Loss_D: 0.10173896700143814 ,Loss_G: 7.290731430053711 ,D(x): 0.9957497119903564 ,D(G(z)) 37.95397035029524\n",
      "epoch: 68 ,i: 400 ,Loss_D: 0.07541387528181076 ,Loss_G: 5.024686813354492 ,D(x): 0.9688342809677124 ,D(G(z)) 1.7125533271090823\n",
      "epoch: 68 ,i: 450 ,Loss_D: 0.0684037059545517 ,Loss_G: 5.714702606201172 ,D(x): 0.940548300743103 ,D(G(z)) 0.1651495462094242\n",
      "epoch: 68 ,i: 500 ,Loss_D: 0.0480804406106472 ,Loss_G: 5.818821430206299 ,D(x): 0.9906456470489502 ,D(G(z)) 3.318504578920782\n",
      "epoch: 68 ,i: 550 ,Loss_D: 0.02229376882314682 ,Loss_G: 6.593515872955322 ,D(x): 0.9844223260879517 ,D(G(z)) 1.0191205661357712\n",
      "epoch: 68 ,i: 600 ,Loss_D: 0.4276077449321747 ,Loss_G: 4.588048934936523 ,D(x): 0.9314877986907959 ,D(G(z)) 5.920666206802764\n",
      "epoch: 68 ,i: 650 ,Loss_D: 0.021702110767364502 ,Loss_G: 6.728570461273193 ,D(x): 0.9885417222976685 ,D(G(z)) 2.0736643271120894\n",
      "epoch: 68 ,i: 700 ,Loss_D: 2.103184700012207 ,Loss_G: 14.370771408081055 ,D(x): 0.9998980760574341 ,D(G(z)) 142672.1857542416\n",
      "epoch: 68 ,i: 750 ,Loss_D: 0.055356189608573914 ,Loss_G: 7.305756568908691 ,D(x): 0.9928457736968994 ,D(G(z)) 16.427022159050804\n",
      "epoch: 69 ,i: 0 ,Loss_D: 0.08207063376903534 ,Loss_G: 6.617600917816162 ,D(x): 0.9930981397628784 ,D(G(z)) 24.61536846406411\n",
      "epoch: 69 ,i: 50 ,Loss_D: 0.03949858248233795 ,Loss_G: 7.09074068069458 ,D(x): 0.9976640939712524 ,D(G(z)) 11.496500915490515\n",
      "epoch: 69 ,i: 100 ,Loss_D: 0.0734955370426178 ,Loss_G: 5.9376678466796875 ,D(x): 0.9409816861152649 ,D(G(z)) 0.21356414454666378\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 69 ,i: 150 ,Loss_D: 0.08140510320663452 ,Loss_G: 6.464399814605713 ,D(x): 0.933921754360199 ,D(G(z)) 0.41097965145542875\n",
      "epoch: 69 ,i: 200 ,Loss_D: 0.26182010769844055 ,Loss_G: 3.8840317726135254 ,D(x): 0.8688791990280151 ,D(G(z)) 0.8171797642184127\n",
      "epoch: 69 ,i: 250 ,Loss_D: 0.09950058907270432 ,Loss_G: 4.463972568511963 ,D(x): 0.9979643821716309 ,D(G(z)) 3.4725524174842612\n",
      "epoch: 69 ,i: 300 ,Loss_D: 0.07101172208786011 ,Loss_G: 5.501497268676758 ,D(x): 0.9394190907478333 ,D(G(z)) 0.3160971342422028\n",
      "epoch: 69 ,i: 350 ,Loss_D: 0.3074248433113098 ,Loss_G: 6.063619136810303 ,D(x): 0.900103747844696 ,D(G(z)) 8.303447028846339\n",
      "epoch: 69 ,i: 400 ,Loss_D: 0.26831403374671936 ,Loss_G: 4.046826362609863 ,D(x): 0.8008610010147095 ,D(G(z)) 0.033759912484484095\n",
      "epoch: 69 ,i: 450 ,Loss_D: 0.03269572556018829 ,Loss_G: 6.9198713302612305 ,D(x): 0.9877538681030273 ,D(G(z)) 5.404723139690973\n",
      "epoch: 69 ,i: 500 ,Loss_D: 0.05035032331943512 ,Loss_G: 5.737785339355469 ,D(x): 0.974181056022644 ,D(G(z)) 2.004006539688009\n",
      "epoch: 69 ,i: 550 ,Loss_D: 0.04613630473613739 ,Loss_G: 4.824889183044434 ,D(x): 0.9629958868026733 ,D(G(z)) 0.3172463442695784\n",
      "epoch: 69 ,i: 600 ,Loss_D: 0.41399794816970825 ,Loss_G: 3.2367160320281982 ,D(x): 0.8355129957199097 ,D(G(z)) 1.621206688007713\n",
      "epoch: 69 ,i: 650 ,Loss_D: 0.0855640396475792 ,Loss_G: 4.67968225479126 ,D(x): 0.9837719202041626 ,D(G(z)) 2.6976037077412163\n",
      "epoch: 69 ,i: 700 ,Loss_D: 0.44725459814071655 ,Loss_G: 6.22374153137207 ,D(x): 0.7013731002807617 ,D(G(z)) 0.03687958718581535\n",
      "epoch: 69 ,i: 750 ,Loss_D: 0.03733235225081444 ,Loss_G: 6.043344497680664 ,D(x): 0.9746346473693848 ,D(G(z)) 1.2030395541000625\n",
      "epoch: 70 ,i: 0 ,Loss_D: 1.0043742656707764 ,Loss_G: 10.141551971435547 ,D(x): 0.999598503112793 ,D(G(z)) 2083.4485580130277\n",
      "epoch: 70 ,i: 50 ,Loss_D: 0.04293224588036537 ,Loss_G: 7.477418899536133 ,D(x): 0.9736284017562866 ,D(G(z)) 1.5946882793549475\n",
      "epoch: 70 ,i: 100 ,Loss_D: 0.11330664157867432 ,Loss_G: 5.128697872161865 ,D(x): 0.9117615818977356 ,D(G(z)) 0.4474654715216871\n",
      "epoch: 70 ,i: 150 ,Loss_D: 0.04774622246623039 ,Loss_G: 4.9335103034973145 ,D(x): 0.994157612323761 ,D(G(z)) 2.6846989643667567\n",
      "epoch: 70 ,i: 200 ,Loss_D: 0.028427258133888245 ,Loss_G: 7.236291885375977 ,D(x): 0.9837080240249634 ,D(G(z)) 2.680240368655503\n",
      "epoch: 70 ,i: 250 ,Loss_D: 0.1187601312994957 ,Loss_G: 5.17946195602417 ,D(x): 0.899587094783783 ,D(G(z)) 0.09577808733759524\n",
      "epoch: 70 ,i: 300 ,Loss_D: 0.22283262014389038 ,Loss_G: 4.04531192779541 ,D(x): 0.8401733636856079 ,D(G(z)) 0.1357169012750738\n",
      "epoch: 70 ,i: 350 ,Loss_D: 0.058337464928627014 ,Loss_G: 6.165050983428955 ,D(x): 0.9612358212471008 ,D(G(z)) 1.326178908008527\n",
      "epoch: 70 ,i: 400 ,Loss_D: 0.04669276252388954 ,Loss_G: 6.188240051269531 ,D(x): 0.9590044021606445 ,D(G(z)) 0.5148612476390743\n",
      "epoch: 70 ,i: 450 ,Loss_D: 0.0699920579791069 ,Loss_G: 6.155396938323975 ,D(x): 0.9410290718078613 ,D(G(z)) 0.27301074836410893\n",
      "epoch: 70 ,i: 500 ,Loss_D: 0.010012066923081875 ,Loss_G: 6.121443748474121 ,D(x): 0.99801105260849 ,D(G(z)) 1.3325647370899931\n",
      "epoch: 70 ,i: 550 ,Loss_D: 0.02080667018890381 ,Loss_G: 6.460719108581543 ,D(x): 0.9887593388557434 ,D(G(z)) 1.7594060982551574\n",
      "epoch: 70 ,i: 600 ,Loss_D: 0.040137387812137604 ,Loss_G: 5.900415897369385 ,D(x): 0.968490719795227 ,D(G(z)) 0.49513072392707186\n",
      "epoch: 70 ,i: 650 ,Loss_D: 0.6272611021995544 ,Loss_G: 12.425841331481934 ,D(x): 0.9954942464828491 ,D(G(z)) 14411.832231986182\n",
      "epoch: 70 ,i: 700 ,Loss_D: 0.09515020996332169 ,Loss_G: 5.681396484375 ,D(x): 0.9199037551879883 ,D(G(z)) 0.21651688814251982\n",
      "epoch: 70 ,i: 750 ,Loss_D: 0.04235735908150673 ,Loss_G: 5.754702568054199 ,D(x): 0.9821224808692932 ,D(G(z)) 1.9872217800731569\n",
      "epoch: 71 ,i: 0 ,Loss_D: 0.056978438049554825 ,Loss_G: 7.068336486816406 ,D(x): 0.9589974880218506 ,D(G(z)) 0.8222478765653282\n",
      "epoch: 71 ,i: 50 ,Loss_D: 0.017878200858831406 ,Loss_G: 6.057903289794922 ,D(x): 0.9914757013320923 ,D(G(z)) 1.2118043780371588\n",
      "epoch: 71 ,i: 100 ,Loss_D: 0.06912378966808319 ,Loss_G: 7.141778469085693 ,D(x): 0.9994853734970093 ,D(G(z)) 31.67851789973777\n",
      "epoch: 71 ,i: 150 ,Loss_D: 0.016137536615133286 ,Loss_G: 6.666128158569336 ,D(x): 0.9920575618743896 ,D(G(z)) 1.487071769198839\n",
      "epoch: 71 ,i: 200 ,Loss_D: 1.697716236114502 ,Loss_G: 0.5451561808586121 ,D(x): 0.33024904131889343 ,D(G(z)) 0.11379507264928049\n",
      "epoch: 71 ,i: 250 ,Loss_D: 0.20378001034259796 ,Loss_G: 4.051879405975342 ,D(x): 0.9255616664886475 ,D(G(z)) 2.4616871968629597\n",
      "epoch: 71 ,i: 300 ,Loss_D: 0.11409354209899902 ,Loss_G: 5.7398295402526855 ,D(x): 0.9775379300117493 ,D(G(z)) 9.13378302551361\n",
      "epoch: 71 ,i: 350 ,Loss_D: 0.0889303907752037 ,Loss_G: 5.753728866577148 ,D(x): 0.9671010375022888 ,D(G(z)) 5.439728698616785\n",
      "epoch: 71 ,i: 400 ,Loss_D: 0.17976681888103485 ,Loss_G: 7.066634178161621 ,D(x): 0.9981042742729187 ,D(G(z)) 97.83667582877153\n",
      "epoch: 71 ,i: 450 ,Loss_D: 0.09062397480010986 ,Loss_G: 4.830403804779053 ,D(x): 0.9672583341598511 ,D(G(z)) 1.876944426174532\n",
      "epoch: 71 ,i: 500 ,Loss_D: 0.06248723715543747 ,Loss_G: 6.231206893920898 ,D(x): 0.9949817657470703 ,D(G(z)) 9.522663583104162\n",
      "epoch: 71 ,i: 550 ,Loss_D: 0.0349336639046669 ,Loss_G: 6.424408912658691 ,D(x): 0.9840842485427856 ,D(G(z)) 3.1485703494727493\n",
      "epoch: 71 ,i: 600 ,Loss_D: 0.46497806906700134 ,Loss_G: 2.7822887897491455 ,D(x): 0.7577774524688721 ,D(G(z)) 0.8368518142620062\n",
      "epoch: 71 ,i: 650 ,Loss_D: 0.2070368081331253 ,Loss_G: 6.009675025939941 ,D(x): 0.9986824989318848 ,D(G(z)) 27.39512350328916\n",
      "epoch: 71 ,i: 700 ,Loss_D: 0.08885732293128967 ,Loss_G: 6.885870933532715 ,D(x): 0.9319769144058228 ,D(G(z)) 0.46909064908183906\n",
      "epoch: 71 ,i: 750 ,Loss_D: 0.03356665372848511 ,Loss_G: 6.453357219696045 ,D(x): 0.9897254705429077 ,D(G(z)) 4.529616074007541\n",
      "epoch: 72 ,i: 0 ,Loss_D: 0.5265413522720337 ,Loss_G: 15.920635223388672 ,D(x): 0.9999337196350098 ,D(G(z)) 852116.7115719337\n",
      "epoch: 72 ,i: 50 ,Loss_D: 0.07746972143650055 ,Loss_G: 5.92881441116333 ,D(x): 0.9486004114151001 ,D(G(z)) 1.8637652790148052\n",
      "epoch: 72 ,i: 100 ,Loss_D: 0.04464833065867424 ,Loss_G: 7.207409858703613 ,D(x): 0.9612286686897278 ,D(G(z)) 0.6389069515107448\n",
      "epoch: 72 ,i: 150 ,Loss_D: 0.027086270973086357 ,Loss_G: 6.089156150817871 ,D(x): 0.9778658151626587 ,D(G(z)) 0.5561328818627085\n",
      "epoch: 72 ,i: 200 ,Loss_D: 0.037809066474437714 ,Loss_G: 5.832914352416992 ,D(x): 0.9758227467536926 ,D(G(z)) 0.9909405968072488\n",
      "epoch: 72 ,i: 250 ,Loss_D: 0.03825381398200989 ,Loss_G: 7.5077104568481445 ,D(x): 0.9903567433357239 ,D(G(z)) 8.493336640239411\n",
      "epoch: 72 ,i: 300 ,Loss_D: 0.32328087091445923 ,Loss_G: 3.798668146133423 ,D(x): 0.7962624430656433 ,D(G(z)) 0.12229284491683762\n",
      "epoch: 72 ,i: 350 ,Loss_D: 0.0532817579805851 ,Loss_G: 4.813861846923828 ,D(x): 0.9831030368804932 ,D(G(z)) 1.61893743407379\n",
      "epoch: 72 ,i: 400 ,Loss_D: 0.3289613425731659 ,Loss_G: 4.445562362670898 ,D(x): 0.9123663902282715 ,D(G(z)) 2.4631595749002604\n",
      "epoch: 72 ,i: 450 ,Loss_D: 0.03389400243759155 ,Loss_G: 6.038530349731445 ,D(x): 0.9845378994941711 ,D(G(z)) 2.3332410341688923\n",
      "epoch: 72 ,i: 500 ,Loss_D: 0.24098578095436096 ,Loss_G: 8.424153327941895 ,D(x): 0.9891617894172668 ,D(G(z)) 353.80186051129357\n",
      "epoch: 72 ,i: 550 ,Loss_D: 0.04970615357160568 ,Loss_G: 5.6436920166015625 ,D(x): 0.9696475267410278 ,D(G(z)) 0.8136604123342214\n",
      "epoch: 72 ,i: 600 ,Loss_D: 0.05967624485492706 ,Loss_G: 4.661922454833984 ,D(x): 0.9706558585166931 ,D(G(z)) 0.9003402803627388\n",
      "epoch: 72 ,i: 650 ,Loss_D: 0.03153446316719055 ,Loss_G: 6.364133834838867 ,D(x): 0.9947088360786438 ,D(G(z)) 3.468348609132699\n",
      "epoch: 72 ,i: 700 ,Loss_D: 0.026996394619345665 ,Loss_G: 6.684107780456543 ,D(x): 0.9927210211753845 ,D(G(z)) 5.433753554376739\n",
      "epoch: 72 ,i: 750 ,Loss_D: 0.12006314843893051 ,Loss_G: 5.935196876525879 ,D(x): 0.9950351715087891 ,D(G(z)) 11.683145300148594\n",
      "epoch: 73 ,i: 0 ,Loss_D: 0.10152865946292877 ,Loss_G: 4.130136489868164 ,D(x): 0.9420309066772461 ,D(G(z)) 0.8300874235790368\n",
      "epoch: 73 ,i: 50 ,Loss_D: 0.06444357335567474 ,Loss_G: 6.036698341369629 ,D(x): 0.9905296564102173 ,D(G(z)) 8.431698609356356\n",
      "epoch: 73 ,i: 100 ,Loss_D: 0.018162375316023827 ,Loss_G: 6.283034324645996 ,D(x): 0.9863019585609436 ,D(G(z)) 0.6445151364882302\n",
      "epoch: 73 ,i: 150 ,Loss_D: 0.014641725458204746 ,Loss_G: 6.493330001831055 ,D(x): 0.9936919212341309 ,D(G(z)) 1.3986692475826585\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 73 ,i: 200 ,Loss_D: 0.016754552721977234 ,Loss_G: 6.904953479766846 ,D(x): 0.9985882043838501 ,D(G(z)) 3.2631571776163755\n",
      "epoch: 73 ,i: 250 ,Loss_D: 0.009939026087522507 ,Loss_G: 6.101300239562988 ,D(x): 0.9981493949890137 ,D(G(z)) 1.2343705494956623\n",
      "epoch: 73 ,i: 300 ,Loss_D: 0.04007725790143013 ,Loss_G: 5.85139274597168 ,D(x): 0.989940345287323 ,D(G(z)) 4.536414905808433\n",
      "epoch: 73 ,i: 350 ,Loss_D: 0.024833809584379196 ,Loss_G: 6.598728179931641 ,D(x): 0.9971178770065308 ,D(G(z)) 4.081643265730629\n",
      "epoch: 73 ,i: 400 ,Loss_D: 0.06784703582525253 ,Loss_G: 4.482855796813965 ,D(x): 0.943219006061554 ,D(G(z)) 0.10497585006444048\n",
      "epoch: 73 ,i: 450 ,Loss_D: 0.042118385434150696 ,Loss_G: 8.595220565795898 ,D(x): 0.9615985751152039 ,D(G(z)) 1.1836909140588643\n",
      "epoch: 73 ,i: 500 ,Loss_D: 0.03984878584742546 ,Loss_G: 5.92868709564209 ,D(x): 0.9735609292984009 ,D(G(z)) 1.0405725795367529\n",
      "epoch: 73 ,i: 550 ,Loss_D: 0.011355883441865444 ,Loss_G: 6.962347030639648 ,D(x): 0.9978379011154175 ,D(G(z)) 2.5945826409475914\n",
      "epoch: 73 ,i: 600 ,Loss_D: 0.03430960699915886 ,Loss_G: 7.361531734466553 ,D(x): 0.996912956237793 ,D(G(z)) 17.783779046867565\n",
      "epoch: 73 ,i: 650 ,Loss_D: 0.09123296290636063 ,Loss_G: 6.54759407043457 ,D(x): 0.9703469276428223 ,D(G(z)) 5.679504325527907\n",
      "epoch: 73 ,i: 700 ,Loss_D: 0.48323920369148254 ,Loss_G: 2.6883468627929688 ,D(x): 0.7352191209793091 ,D(G(z)) 0.031355951292803\n",
      "epoch: 73 ,i: 750 ,Loss_D: 0.027855433523654938 ,Loss_G: 7.197885990142822 ,D(x): 0.9799765348434448 ,D(G(z)) 1.5477528068106303\n",
      "epoch: 74 ,i: 0 ,Loss_D: 0.8729022741317749 ,Loss_G: 10.10906982421875 ,D(x): 0.9886600971221924 ,D(G(z)) 2280.188060234871\n",
      "epoch: 74 ,i: 50 ,Loss_D: 0.04540662094950676 ,Loss_G: 6.934483528137207 ,D(x): 0.9858654737472534 ,D(G(z)) 7.940738793873086\n",
      "epoch: 74 ,i: 100 ,Loss_D: 0.9388805627822876 ,Loss_G: 9.385417938232422 ,D(x): 0.9997422695159912 ,D(G(z)) 1306.9214364709487\n",
      "epoch: 74 ,i: 150 ,Loss_D: 0.0568796768784523 ,Loss_G: 7.053689002990723 ,D(x): 0.9855360984802246 ,D(G(z)) 15.306010117240124\n",
      "epoch: 74 ,i: 200 ,Loss_D: 0.20112532377243042 ,Loss_G: 10.516627311706543 ,D(x): 0.9982859492301941 ,D(G(z)) 1745.710322872304\n",
      "epoch: 74 ,i: 250 ,Loss_D: 0.025970973074436188 ,Loss_G: 6.910411357879639 ,D(x): 0.9903750419616699 ,D(G(z)) 3.9691633776329738\n",
      "epoch: 74 ,i: 300 ,Loss_D: 0.02735351212322712 ,Loss_G: 6.296398162841797 ,D(x): 0.9944316148757935 ,D(G(z)) 4.472099129652852\n",
      "epoch: 74 ,i: 350 ,Loss_D: 0.024523165076971054 ,Loss_G: 6.113748550415039 ,D(x): 0.995968222618103 ,D(G(z)) 2.135709690248058\n",
      "epoch: 74 ,i: 400 ,Loss_D: 0.3299340009689331 ,Loss_G: 2.995032787322998 ,D(x): 0.8014940619468689 ,D(G(z)) 0.42555062738888516\n",
      "epoch: 74 ,i: 450 ,Loss_D: 0.14521946012973785 ,Loss_G: 4.273738861083984 ,D(x): 0.8983466625213623 ,D(G(z)) 0.1601083748972173\n",
      "epoch: 74 ,i: 500 ,Loss_D: 0.07927535474300385 ,Loss_G: 4.9707794189453125 ,D(x): 0.9725306034088135 ,D(G(z)) 2.7283294635362045\n",
      "epoch: 74 ,i: 550 ,Loss_D: 0.07451149821281433 ,Loss_G: 6.258330821990967 ,D(x): 0.979149580001831 ,D(G(z)) 8.886323051849836\n",
      "epoch: 74 ,i: 600 ,Loss_D: 0.16278700530529022 ,Loss_G: 4.688076019287109 ,D(x): 0.8956350088119507 ,D(G(z)) 0.3677175074273591\n",
      "epoch: 74 ,i: 650 ,Loss_D: 0.06840917468070984 ,Loss_G: 5.870959281921387 ,D(x): 0.9742774367332458 ,D(G(z)) 3.433284027411945\n",
      "epoch: 74 ,i: 700 ,Loss_D: 0.06539766490459442 ,Loss_G: 7.340456008911133 ,D(x): 0.9838838577270508 ,D(G(z)) 19.63902232896942\n",
      "epoch: 74 ,i: 750 ,Loss_D: 0.02840232476592064 ,Loss_G: 5.975497245788574 ,D(x): 0.987657904624939 ,D(G(z)) 1.825594709135768\n",
      "epoch: 75 ,i: 0 ,Loss_D: 0.035865701735019684 ,Loss_G: 6.166347503662109 ,D(x): 0.977715253829956 ,D(G(z)) 1.2180440600885303\n",
      "epoch: 75 ,i: 50 ,Loss_D: 0.2220667451620102 ,Loss_G: 11.865291595458984 ,D(x): 0.8365229368209839 ,D(G(z)) 1.10762319706223\n",
      "epoch: 75 ,i: 100 ,Loss_D: 0.0351797416806221 ,Loss_G: 6.763464450836182 ,D(x): 0.9702086448669434 ,D(G(z)) 0.4696056621972732\n",
      "epoch: 75 ,i: 150 ,Loss_D: 0.05475686118006706 ,Loss_G: 6.112959384918213 ,D(x): 0.9569594264030457 ,D(G(z)) 0.7094198442292656\n",
      "epoch: 75 ,i: 200 ,Loss_D: 0.20939208567142487 ,Loss_G: 9.525522232055664 ,D(x): 0.9994515180587769 ,D(G(z)) 728.8316326925145\n",
      "epoch: 75 ,i: 250 ,Loss_D: 0.008515017107129097 ,Loss_G: 7.546688556671143 ,D(x): 0.9938476085662842 ,D(G(z)) 1.0847909153278619\n",
      "epoch: 75 ,i: 300 ,Loss_D: 0.054873429238796234 ,Loss_G: 5.842695713043213 ,D(x): 0.9888800382614136 ,D(G(z)) 5.485524068175511\n",
      "epoch: 75 ,i: 350 ,Loss_D: 0.017207052558660507 ,Loss_G: 7.539454936981201 ,D(x): 0.9857355356216431 ,D(G(z)) 0.7153948135127338\n",
      "epoch: 75 ,i: 400 ,Loss_D: 0.148304283618927 ,Loss_G: 8.824472427368164 ,D(x): 0.9965791702270508 ,D(G(z)) 365.9348889201528\n",
      "epoch: 75 ,i: 450 ,Loss_D: 0.025292620062828064 ,Loss_G: 6.143770217895508 ,D(x): 0.9779856204986572 ,D(G(z)) 0.35652708687710216\n",
      "epoch: 75 ,i: 500 ,Loss_D: 0.008718356490135193 ,Loss_G: 6.489365100860596 ,D(x): 0.9966915845870972 ,D(G(z)) 1.2614279398172241\n",
      "epoch: 75 ,i: 550 ,Loss_D: 0.21228906512260437 ,Loss_G: 5.792603015899658 ,D(x): 0.9502495527267456 ,D(G(z)) 13.144740767077554\n",
      "epoch: 75 ,i: 600 ,Loss_D: 0.07531772553920746 ,Loss_G: 6.278655529022217 ,D(x): 0.9928447604179382 ,D(G(z)) 10.619838625339119\n",
      "epoch: 75 ,i: 650 ,Loss_D: 0.047206878662109375 ,Loss_G: 6.058594703674316 ,D(x): 0.9928445816040039 ,D(G(z)) 6.175705179971042\n",
      "epoch: 75 ,i: 700 ,Loss_D: 0.02837948501110077 ,Loss_G: 7.010628700256348 ,D(x): 0.982336163520813 ,D(G(z)) 2.719809645153267\n",
      "epoch: 75 ,i: 750 ,Loss_D: 0.04033612087368965 ,Loss_G: 6.732239723205566 ,D(x): 0.9877109527587891 ,D(G(z)) 5.680712538458678\n",
      "epoch: 76 ,i: 0 ,Loss_D: 0.048540543764829636 ,Loss_G: 7.510550022125244 ,D(x): 0.9573298096656799 ,D(G(z)) 0.46567986308382603\n",
      "epoch: 76 ,i: 50 ,Loss_D: 0.010496691800653934 ,Loss_G: 8.33854866027832 ,D(x): 0.9912588596343994 ,D(G(z)) 1.0618660987991755\n",
      "epoch: 76 ,i: 100 ,Loss_D: 0.1551092565059662 ,Loss_G: 5.901289939880371 ,D(x): 0.9592497944831848 ,D(G(z)) 16.340538249100945\n",
      "epoch: 76 ,i: 150 ,Loss_D: 0.14582763612270355 ,Loss_G: 5.975467681884766 ,D(x): 0.9954050183296204 ,D(G(z)) 8.300844891729778\n",
      "epoch: 76 ,i: 200 ,Loss_D: 0.18776369094848633 ,Loss_G: 6.994645595550537 ,D(x): 0.992951512336731 ,D(G(z)) 42.58289690179673\n",
      "epoch: 76 ,i: 250 ,Loss_D: 0.20006278157234192 ,Loss_G: 3.582122325897217 ,D(x): 0.8840213418006897 ,D(G(z)) 0.6191338450576376\n",
      "epoch: 76 ,i: 300 ,Loss_D: 0.08417932689189911 ,Loss_G: 4.75937032699585 ,D(x): 0.978509783744812 ,D(G(z)) 1.3292963315692174\n",
      "epoch: 76 ,i: 350 ,Loss_D: 0.08590461313724518 ,Loss_G: 6.970598220825195 ,D(x): 0.9899318218231201 ,D(G(z)) 10.435304599742707\n",
      "epoch: 76 ,i: 400 ,Loss_D: 0.2060195952653885 ,Loss_G: 2.7828283309936523 ,D(x): 0.8691103458404541 ,D(G(z)) 0.09459313218898195\n",
      "epoch: 76 ,i: 450 ,Loss_D: 0.19868764281272888 ,Loss_G: 5.6194610595703125 ,D(x): 0.8826454877853394 ,D(G(z)) 0.6307886808464528\n",
      "epoch: 76 ,i: 500 ,Loss_D: 0.11981947720050812 ,Loss_G: 5.110655784606934 ,D(x): 0.9103483557701111 ,D(G(z)) 0.36756604090484885\n",
      "epoch: 76 ,i: 550 ,Loss_D: 0.015077797695994377 ,Loss_G: 5.094245910644531 ,D(x): 0.9953100681304932 ,D(G(z)) 0.4857228102549366\n",
      "epoch: 76 ,i: 600 ,Loss_D: 0.008934466168284416 ,Loss_G: 6.295085906982422 ,D(x): 0.997229814529419 ,D(G(z)) 1.0766019994432463\n",
      "epoch: 76 ,i: 650 ,Loss_D: 0.3089769184589386 ,Loss_G: 10.834237098693848 ,D(x): 0.9997209310531616 ,D(G(z)) 2165.7771690868535\n",
      "epoch: 76 ,i: 700 ,Loss_D: 0.03088715486228466 ,Loss_G: 6.3487653732299805 ,D(x): 0.9940252900123596 ,D(G(z)) 5.636630203670323\n",
      "epoch: 76 ,i: 750 ,Loss_D: 0.014989146962761879 ,Loss_G: 6.127021789550781 ,D(x): 0.9951796531677246 ,D(G(z)) 1.338393999745539\n",
      "epoch: 77 ,i: 0 ,Loss_D: 0.2728947699069977 ,Loss_G: 4.051772117614746 ,D(x): 0.8581864833831787 ,D(G(z)) 0.7594292989209823\n",
      "epoch: 77 ,i: 50 ,Loss_D: 0.273336797952652 ,Loss_G: 8.686102867126465 ,D(x): 0.8036091327667236 ,D(G(z)) 0.2730649926272172\n",
      "epoch: 77 ,i: 100 ,Loss_D: 0.08352083712816238 ,Loss_G: 6.614234924316406 ,D(x): 0.9315900802612305 ,D(G(z)) 0.5075432634109965\n",
      "epoch: 77 ,i: 150 ,Loss_D: 0.0935724675655365 ,Loss_G: 5.389622688293457 ,D(x): 0.9281096458435059 ,D(G(z)) 0.6406593211733684\n",
      "epoch: 77 ,i: 200 ,Loss_D: 0.03623555600643158 ,Loss_G: 6.56302547454834 ,D(x): 0.9951001405715942 ,D(G(z)) 6.443904670609896\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 77 ,i: 250 ,Loss_D: 0.347025603055954 ,Loss_G: 2.9720327854156494 ,D(x): 0.7992015480995178 ,D(G(z)) 0.056981691504793396\n",
      "epoch: 77 ,i: 300 ,Loss_D: 0.10757850110530853 ,Loss_G: 4.112261772155762 ,D(x): 0.9378273487091064 ,D(G(z)) 0.6010307890889293\n",
      "epoch: 77 ,i: 350 ,Loss_D: 0.3197101950645447 ,Loss_G: 4.7760419845581055 ,D(x): 0.7782242298126221 ,D(G(z)) 0.3893965223155315\n",
      "epoch: 77 ,i: 400 ,Loss_D: 0.043022919446229935 ,Loss_G: 6.858773231506348 ,D(x): 0.9661552906036377 ,D(G(z)) 0.9987446367892894\n",
      "epoch: 77 ,i: 450 ,Loss_D: 0.016668880358338356 ,Loss_G: 6.759153842926025 ,D(x): 0.9982228875160217 ,D(G(z)) 3.208375362209886\n",
      "epoch: 77 ,i: 500 ,Loss_D: 0.08517998456954956 ,Loss_G: 5.334403038024902 ,D(x): 0.9333916306495667 ,D(G(z)) 0.2907423280195968\n",
      "epoch: 77 ,i: 550 ,Loss_D: 0.008734543807804585 ,Loss_G: 10.768327713012695 ,D(x): 0.9919845461845398 ,D(G(z)) 5.092890094745301\n",
      "epoch: 77 ,i: 600 ,Loss_D: 0.012662606313824654 ,Loss_G: 6.445367336273193 ,D(x): 0.9914621114730835 ,D(G(z)) 0.728450753314355\n",
      "epoch: 77 ,i: 650 ,Loss_D: 0.020589102059602737 ,Loss_G: 8.367925643920898 ,D(x): 0.9841105937957764 ,D(G(z)) 4.114204171699488\n",
      "epoch: 77 ,i: 700 ,Loss_D: 0.028318636119365692 ,Loss_G: 6.971785545349121 ,D(x): 0.997036874294281 ,D(G(z)) 8.23325982365663\n",
      "epoch: 77 ,i: 750 ,Loss_D: 0.043200813233852386 ,Loss_G: 7.602500915527344 ,D(x): 0.9959378242492676 ,D(G(z)) 21.06474824263154\n",
      "epoch: 78 ,i: 0 ,Loss_D: 0.017874928191304207 ,Loss_G: 6.607491493225098 ,D(x): 0.9989796876907349 ,D(G(z)) 3.669587285784335\n",
      "epoch: 78 ,i: 50 ,Loss_D: 0.2256707400083542 ,Loss_G: 5.821622848510742 ,D(x): 0.9603563547134399 ,D(G(z)) 16.547142337383928\n",
      "epoch: 78 ,i: 100 ,Loss_D: 0.08111389726400375 ,Loss_G: 6.502298355102539 ,D(x): 0.949485182762146 ,D(G(z)) 2.3185697316803933\n",
      "epoch: 78 ,i: 150 ,Loss_D: 0.017163725569844246 ,Loss_G: 7.026749134063721 ,D(x): 0.9902290105819702 ,D(G(z)) 2.0953730827130403\n",
      "epoch: 78 ,i: 200 ,Loss_D: 0.09869840741157532 ,Loss_G: 5.443015098571777 ,D(x): 0.9397813081741333 ,D(G(z)) 1.2450805917554084\n",
      "epoch: 78 ,i: 250 ,Loss_D: 0.027597203850746155 ,Loss_G: 7.969809532165527 ,D(x): 0.9799454212188721 ,D(G(z)) 3.301674575030171\n",
      "epoch: 78 ,i: 300 ,Loss_D: 0.028412343934178352 ,Loss_G: 5.974592208862305 ,D(x): 0.9830110669136047 ,D(G(z)) 0.9404990431741576\n",
      "epoch: 78 ,i: 350 ,Loss_D: 0.06779977679252625 ,Loss_G: 5.86016845703125 ,D(x): 0.9417879581451416 ,D(G(z)) 0.24966759332644478\n",
      "epoch: 78 ,i: 400 ,Loss_D: 0.022213175892829895 ,Loss_G: 6.900861740112305 ,D(x): 0.9982470870018005 ,D(G(z)) 3.555978138877243\n",
      "epoch: 78 ,i: 450 ,Loss_D: 1.490085482597351 ,Loss_G: 2.460080146789551 ,D(x): 0.39521050453186035 ,D(G(z)) 0.0024141626558267606\n",
      "epoch: 78 ,i: 500 ,Loss_D: 0.10011520981788635 ,Loss_G: 6.625278472900391 ,D(x): 0.9318654537200928 ,D(G(z)) 0.787673906341207\n",
      "epoch: 78 ,i: 550 ,Loss_D: 0.044959329068660736 ,Loss_G: 5.562973976135254 ,D(x): 0.9801837801933289 ,D(G(z)) 2.3776568948154106\n",
      "epoch: 78 ,i: 600 ,Loss_D: 0.045811302959918976 ,Loss_G: 5.386486053466797 ,D(x): 0.9981406927108765 ,D(G(z)) 2.4404695025280443\n",
      "epoch: 78 ,i: 650 ,Loss_D: 0.026317037642002106 ,Loss_G: 8.315397262573242 ,D(x): 0.9900723695755005 ,D(G(z)) 9.050049104263595\n",
      "epoch: 78 ,i: 700 ,Loss_D: 0.3889094591140747 ,Loss_G: 6.389825820922852 ,D(x): 0.9785466194152832 ,D(G(z)) 53.98353868756281\n",
      "epoch: 78 ,i: 750 ,Loss_D: 0.02808469533920288 ,Loss_G: 6.289329528808594 ,D(x): 0.9865797758102417 ,D(G(z)) 1.874971879729427\n",
      "epoch: 79 ,i: 0 ,Loss_D: 0.2965463697910309 ,Loss_G: 8.944107055664062 ,D(x): 0.9991649985313416 ,D(G(z)) 326.59859838177624\n",
      "epoch: 79 ,i: 50 ,Loss_D: 0.010784100741147995 ,Loss_G: 7.187065124511719 ,D(x): 0.9929929971694946 ,D(G(z)) 1.342191918481445\n",
      "epoch: 79 ,i: 100 ,Loss_D: 0.15830044448375702 ,Loss_G: 5.709473609924316 ,D(x): 0.9767806529998779 ,D(G(z)) 7.304907748780598\n",
      "epoch: 79 ,i: 150 ,Loss_D: 0.01519402302801609 ,Loss_G: 7.238437175750732 ,D(x): 0.9980416297912598 ,D(G(z)) 3.706240024165119\n",
      "epoch: 79 ,i: 200 ,Loss_D: 0.14810404181480408 ,Loss_G: 4.947035312652588 ,D(x): 0.9957168102264404 ,D(G(z)) 5.012239893250131\n",
      "epoch: 79 ,i: 250 ,Loss_D: 0.1741597205400467 ,Loss_G: 5.013561248779297 ,D(x): 0.9003962278366089 ,D(G(z)) 0.29946993192345933\n",
      "epoch: 79 ,i: 300 ,Loss_D: 0.01731242425739765 ,Loss_G: 7.012170791625977 ,D(x): 0.9949066638946533 ,D(G(z)) 2.9420429853611347\n",
      "epoch: 79 ,i: 350 ,Loss_D: 0.03261158987879753 ,Loss_G: 5.388103485107422 ,D(x): 0.9891827702522278 ,D(G(z)) 1.3088926094006352\n",
      "epoch: 79 ,i: 400 ,Loss_D: 0.03249090164899826 ,Loss_G: 6.717839241027832 ,D(x): 0.9945881366729736 ,D(G(z)) 5.113145440743789\n",
      "epoch: 79 ,i: 450 ,Loss_D: 0.04068874195218086 ,Loss_G: 6.550400733947754 ,D(x): 0.9643619060516357 ,D(G(z)) 0.3827371173790149\n",
      "epoch: 79 ,i: 500 ,Loss_D: 0.02546617016196251 ,Loss_G: 7.013721466064453 ,D(x): 0.9983606338500977 ,D(G(z)) 7.386622674074844\n",
      "epoch: 79 ,i: 550 ,Loss_D: 0.025723520666360855 ,Loss_G: 6.033963203430176 ,D(x): 0.9881699085235596 ,D(G(z)) 1.4581312511598663\n",
      "epoch: 79 ,i: 600 ,Loss_D: 0.012319017201662064 ,Loss_G: 8.309432983398438 ,D(x): 0.9884891510009766 ,D(G(z)) 0.8481684238733816\n",
      "epoch: 79 ,i: 650 ,Loss_D: 0.009900202974677086 ,Loss_G: 6.7970380783081055 ,D(x): 0.9958919882774353 ,D(G(z)) 1.589348219307\n",
      "epoch: 79 ,i: 700 ,Loss_D: 0.09528504312038422 ,Loss_G: 5.309985637664795 ,D(x): 0.9235724210739136 ,D(G(z)) 0.10561739263897987\n",
      "epoch: 79 ,i: 750 ,Loss_D: 0.03953339904546738 ,Loss_G: 5.520346641540527 ,D(x): 0.9762016534805298 ,D(G(z)) 1.122997790049797\n",
      "epoch: 80 ,i: 0 ,Loss_D: 5.5074567794799805 ,Loss_G: 20.53377914428711 ,D(x): 0.9999990463256836 ,D(G(z)) 10707278.390661428\n",
      "epoch: 80 ,i: 50 ,Loss_D: 0.672443687915802 ,Loss_G: 8.116182327270508 ,D(x): 0.9942700862884521 ,D(G(z)) 512.827586888698\n",
      "epoch: 80 ,i: 100 ,Loss_D: 0.12362271547317505 ,Loss_G: 6.190743446350098 ,D(x): 0.9908064603805542 ,D(G(z)) 15.294158903255985\n",
      "epoch: 80 ,i: 150 ,Loss_D: 0.4464688301086426 ,Loss_G: 7.313675880432129 ,D(x): 0.9916931986808777 ,D(G(z)) 97.83423980570566\n",
      "epoch: 80 ,i: 200 ,Loss_D: 0.1760387420654297 ,Loss_G: 7.165932655334473 ,D(x): 0.9356264472007751 ,D(G(z)) 21.998697881851967\n",
      "epoch: 80 ,i: 250 ,Loss_D: 0.1572885513305664 ,Loss_G: 5.187772750854492 ,D(x): 0.8997623920440674 ,D(G(z)) 1.1491514262192764\n",
      "epoch: 80 ,i: 300 ,Loss_D: 0.13009366393089294 ,Loss_G: 7.010817527770996 ,D(x): 0.9592236280441284 ,D(G(z)) 20.855813204940787\n",
      "epoch: 80 ,i: 350 ,Loss_D: 0.4435300827026367 ,Loss_G: 10.024272918701172 ,D(x): 0.9984368085861206 ,D(G(z)) 1916.6757714270445\n",
      "epoch: 80 ,i: 400 ,Loss_D: 0.14542143046855927 ,Loss_G: 8.74896240234375 ,D(x): 0.8857331275939941 ,D(G(z)) 0.7033335786524546\n",
      "epoch: 80 ,i: 450 ,Loss_D: 0.061200279742479324 ,Loss_G: 4.896658897399902 ,D(x): 0.9567450284957886 ,D(G(z)) 0.491891515253858\n",
      "epoch: 80 ,i: 500 ,Loss_D: 0.02914775162935257 ,Loss_G: 6.247969150543213 ,D(x): 0.9863657355308533 ,D(G(z)) 2.23356362983728\n",
      "epoch: 80 ,i: 550 ,Loss_D: 0.20095603168010712 ,Loss_G: 5.220646381378174 ,D(x): 0.9489462375640869 ,D(G(z)) 8.075812034751724\n",
      "epoch: 80 ,i: 600 ,Loss_D: 0.08606234192848206 ,Loss_G: 7.278844833374023 ,D(x): 0.9614588022232056 ,D(G(z)) 8.824583767426725\n",
      "epoch: 80 ,i: 650 ,Loss_D: 0.06635911762714386 ,Loss_G: 5.740128517150879 ,D(x): 0.9818766713142395 ,D(G(z)) 3.4606493622158667\n",
      "epoch: 80 ,i: 700 ,Loss_D: 0.024558795616030693 ,Loss_G: 6.415401935577393 ,D(x): 0.9856385588645935 ,D(G(z)) 1.6674040092158726\n",
      "epoch: 80 ,i: 750 ,Loss_D: 0.018691206350922585 ,Loss_G: 6.778557777404785 ,D(x): 0.9968621134757996 ,D(G(z)) 3.4093797895210516\n",
      "epoch: 81 ,i: 0 ,Loss_D: 0.02620697021484375 ,Loss_G: 6.218829154968262 ,D(x): 0.9975435733795166 ,D(G(z)) 2.9115079609540153\n",
      "epoch: 81 ,i: 50 ,Loss_D: 0.024214396253228188 ,Loss_G: 7.151388645172119 ,D(x): 0.9928723573684692 ,D(G(z)) 5.6418628623509255\n",
      "epoch: 81 ,i: 100 ,Loss_D: 0.16317139565944672 ,Loss_G: 3.855264663696289 ,D(x): 0.8900609016418457 ,D(G(z)) 0.15046377450291074\n",
      "epoch: 81 ,i: 150 ,Loss_D: 0.07473399490118027 ,Loss_G: 6.217981338500977 ,D(x): 0.9986331462860107 ,D(G(z)) 11.244051851308301\n",
      "epoch: 81 ,i: 200 ,Loss_D: 0.04808807745575905 ,Loss_G: 6.132402420043945 ,D(x): 0.9841859340667725 ,D(G(z)) 4.73313911815031\n",
      "epoch: 81 ,i: 250 ,Loss_D: 0.004851330071687698 ,Loss_G: 7.705657958984375 ,D(x): 0.9988312721252441 ,D(G(z)) 1.7195061284498114\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 81 ,i: 300 ,Loss_D: 0.15365083515644073 ,Loss_G: 10.301915168762207 ,D(x): 0.9971212148666382 ,D(G(z)) 1501.7708112614046\n",
      "epoch: 81 ,i: 350 ,Loss_D: 0.041197024285793304 ,Loss_G: 7.064479351043701 ,D(x): 0.9794381856918335 ,D(G(z)) 5.375805230628258\n",
      "epoch: 81 ,i: 400 ,Loss_D: 0.0349775105714798 ,Loss_G: 6.46007776260376 ,D(x): 0.9846358299255371 ,D(G(z)) 2.6760522859047424\n",
      "epoch: 81 ,i: 450 ,Loss_D: 0.13487008213996887 ,Loss_G: 3.554755210876465 ,D(x): 0.8851255774497986 ,D(G(z)) 0.01653460277438354\n",
      "epoch: 81 ,i: 500 ,Loss_D: 0.024524785578250885 ,Loss_G: 6.893442153930664 ,D(x): 0.988205075263977 ,D(G(z)) 2.2993505019385903\n",
      "epoch: 81 ,i: 550 ,Loss_D: 0.5507005453109741 ,Loss_G: 3.515218734741211 ,D(x): 0.6551074981689453 ,D(G(z)) 0.0015764046026915603\n",
      "epoch: 81 ,i: 600 ,Loss_D: 0.06081540882587433 ,Loss_G: 6.507917404174805 ,D(x): 0.966002345085144 ,D(G(z)) 4.348161932317928\n",
      "epoch: 81 ,i: 650 ,Loss_D: 0.5191677808761597 ,Loss_G: 5.1734700202941895 ,D(x): 0.7047595977783203 ,D(G(z)) 0.03454820332713479\n",
      "epoch: 81 ,i: 700 ,Loss_D: 0.04080567508935928 ,Loss_G: 6.278295993804932 ,D(x): 0.9935996532440186 ,D(G(z)) 3.815868968882687\n",
      "epoch: 81 ,i: 750 ,Loss_D: 0.18839551508426666 ,Loss_G: 4.942917346954346 ,D(x): 0.900583803653717 ,D(G(z)) 1.441820065105336\n",
      "epoch: 82 ,i: 0 ,Loss_D: 1.9530986547470093 ,Loss_G: 23.027992248535156 ,D(x): 0.9999773502349854 ,D(G(z)) 142405814.01901793\n",
      "epoch: 82 ,i: 50 ,Loss_D: 0.08938685059547424 ,Loss_G: 4.301144123077393 ,D(x): 0.9707831740379333 ,D(G(z)) 1.0324505849637624\n",
      "epoch: 82 ,i: 100 ,Loss_D: 0.179331436753273 ,Loss_G: 3.5130581855773926 ,D(x): 0.8875980377197266 ,D(G(z)) 0.2719738735958749\n",
      "epoch: 82 ,i: 150 ,Loss_D: 0.09686107188463211 ,Loss_G: 4.631253242492676 ,D(x): 0.931995153427124 ,D(G(z)) 0.26450689226733093\n",
      "epoch: 82 ,i: 200 ,Loss_D: 0.03338252753019333 ,Loss_G: 6.478768348693848 ,D(x): 0.9760375022888184 ,D(G(z)) 1.215152247683837\n",
      "epoch: 82 ,i: 250 ,Loss_D: 0.027611812576651573 ,Loss_G: 6.279305458068848 ,D(x): 0.9969689249992371 ,D(G(z)) 3.270950457765418\n",
      "epoch: 82 ,i: 300 ,Loss_D: 0.03662360459566116 ,Loss_G: 5.715969085693359 ,D(x): 0.9850507378578186 ,D(G(z)) 1.2976181105986142\n",
      "epoch: 82 ,i: 350 ,Loss_D: 0.015995187684893608 ,Loss_G: 6.833402633666992 ,D(x): 0.9874750971794128 ,D(G(z)) 0.9002976680423641\n",
      "epoch: 82 ,i: 400 ,Loss_D: 0.25286629796028137 ,Loss_G: 9.055352210998535 ,D(x): 0.9990226626396179 ,D(G(z)) 715.6918009446878\n",
      "epoch: 82 ,i: 450 ,Loss_D: 0.024354353547096252 ,Loss_G: 6.196475505828857 ,D(x): 0.9974123239517212 ,D(G(z)) 3.80534631958799\n",
      "epoch: 82 ,i: 500 ,Loss_D: 0.039929814636707306 ,Loss_G: 6.294464111328125 ,D(x): 0.9971227645874023 ,D(G(z)) 5.849059935573556\n",
      "epoch: 82 ,i: 550 ,Loss_D: 0.04144662618637085 ,Loss_G: 5.549201965332031 ,D(x): 0.9673643708229065 ,D(G(z)) 0.5333485940851067\n",
      "epoch: 82 ,i: 600 ,Loss_D: 0.017740825191140175 ,Loss_G: 8.243827819824219 ,D(x): 0.9841150641441345 ,D(G(z)) 1.1049284970574837\n",
      "epoch: 82 ,i: 650 ,Loss_D: 0.014516833238303661 ,Loss_G: 7.32161808013916 ,D(x): 0.996288001537323 ,D(G(z)) 4.181769452401495\n",
      "epoch: 82 ,i: 700 ,Loss_D: 0.024972397834062576 ,Loss_G: 7.707705974578857 ,D(x): 0.9793878793716431 ,D(G(z)) 1.5710069470000094\n",
      "epoch: 82 ,i: 750 ,Loss_D: 0.024378571659326553 ,Loss_G: 5.562964916229248 ,D(x): 0.9863806366920471 ,D(G(z)) 0.8213269586978108\n",
      "epoch: 83 ,i: 0 ,Loss_D: 0.16430693864822388 ,Loss_G: 11.051565170288086 ,D(x): 0.9999206066131592 ,D(G(z)) 3773.7938533753777\n",
      "epoch: 83 ,i: 50 ,Loss_D: 0.06788342446088791 ,Loss_G: 5.305290222167969 ,D(x): 0.9544153213500977 ,D(G(z)) 0.5682976285938741\n",
      "epoch: 83 ,i: 100 ,Loss_D: 0.08708193153142929 ,Loss_G: 7.1773786544799805 ,D(x): 0.9995124340057373 ,D(G(z)) 38.48750352980314\n",
      "epoch: 83 ,i: 150 ,Loss_D: 0.2412070780992508 ,Loss_G: 6.372175216674805 ,D(x): 0.9715394973754883 ,D(G(z)) 31.36219483907119\n",
      "epoch: 83 ,i: 200 ,Loss_D: 0.21147380769252777 ,Loss_G: 4.8604230880737305 ,D(x): 0.8696420192718506 ,D(G(z)) 0.34986614923994985\n",
      "epoch: 83 ,i: 250 ,Loss_D: 0.05679450184106827 ,Loss_G: 5.267524719238281 ,D(x): 0.9514246582984924 ,D(G(z)) 0.29391749578869053\n",
      "epoch: 83 ,i: 300 ,Loss_D: 0.04778013378381729 ,Loss_G: 6.654287815093994 ,D(x): 0.9879918694496155 ,D(G(z)) 8.843715701369115\n",
      "epoch: 83 ,i: 350 ,Loss_D: 0.029882658272981644 ,Loss_G: 6.810288429260254 ,D(x): 0.9819462299346924 ,D(G(z)) 1.8903885069435313\n",
      "epoch: 83 ,i: 400 ,Loss_D: 0.3759896755218506 ,Loss_G: 4.173296928405762 ,D(x): 0.8566440939903259 ,D(G(z)) 2.390406688984403\n",
      "epoch: 83 ,i: 450 ,Loss_D: 0.021585123613476753 ,Loss_G: 6.795309066772461 ,D(x): 0.9920885562896729 ,D(G(z)) 1.9535478009357425\n",
      "epoch: 83 ,i: 500 ,Loss_D: 0.030454909428954124 ,Loss_G: 6.965451717376709 ,D(x): 0.9749890565872192 ,D(G(z)) 0.729223924056562\n",
      "epoch: 83 ,i: 550 ,Loss_D: 0.11076319217681885 ,Loss_G: 4.768015384674072 ,D(x): 0.9391844272613525 ,D(G(z)) 1.261892903335282\n",
      "epoch: 83 ,i: 600 ,Loss_D: 0.029006732627749443 ,Loss_G: 8.32712173461914 ,D(x): 0.9748235940933228 ,D(G(z)) 1.458793795182131\n",
      "epoch: 83 ,i: 650 ,Loss_D: 0.008034924976527691 ,Loss_G: 8.182323455810547 ,D(x): 0.9946714639663696 ,D(G(z)) 1.871863649668783\n",
      "epoch: 83 ,i: 700 ,Loss_D: 0.05273082107305527 ,Loss_G: 7.349139213562012 ,D(x): 0.9781845808029175 ,D(G(z)) 6.209922193600844\n",
      "epoch: 83 ,i: 750 ,Loss_D: 0.02924998104572296 ,Loss_G: 7.11850643157959 ,D(x): 0.9747728109359741 ,D(G(z)) 0.6146362272256128\n",
      "epoch: 84 ,i: 0 ,Loss_D: 7.060390949249268 ,Loss_G: 19.43472671508789 ,D(x): 0.9999960064888 ,D(G(z)) 1324737.614106405\n",
      "epoch: 84 ,i: 50 ,Loss_D: 0.14911706745624542 ,Loss_G: 3.3844425678253174 ,D(x): 0.8983754515647888 ,D(G(z)) 0.333249205298899\n",
      "epoch: 84 ,i: 100 ,Loss_D: 0.0763343796133995 ,Loss_G: 5.921982765197754 ,D(x): 0.9747464656829834 ,D(G(z)) 5.877995935725889\n",
      "epoch: 84 ,i: 150 ,Loss_D: 0.2778475284576416 ,Loss_G: 6.411506652832031 ,D(x): 0.8011888265609741 ,D(G(z)) 0.06129713442899284\n",
      "epoch: 84 ,i: 200 ,Loss_D: 0.026790369302034378 ,Loss_G: 7.027971267700195 ,D(x): 0.9831676483154297 ,D(G(z)) 2.1128771309481618\n",
      "epoch: 84 ,i: 250 ,Loss_D: 0.06640971451997757 ,Loss_G: 5.302792549133301 ,D(x): 0.9502149820327759 ,D(G(z)) 0.3778437911127112\n",
      "epoch: 84 ,i: 300 ,Loss_D: 0.1573951691389084 ,Loss_G: 6.954323768615723 ,D(x): 0.993395209312439 ,D(G(z)) 64.48987756187177\n",
      "epoch: 84 ,i: 350 ,Loss_D: 0.023961808532476425 ,Loss_G: 5.573002815246582 ,D(x): 0.9941543340682983 ,D(G(z)) 0.9670336820240552\n",
      "epoch: 84 ,i: 400 ,Loss_D: 0.02146191895008087 ,Loss_G: 7.992384910583496 ,D(x): 0.9850164651870728 ,D(G(z)) 3.7254022362750328\n",
      "epoch: 84 ,i: 450 ,Loss_D: 0.01381718274205923 ,Loss_G: 6.740729808807373 ,D(x): 0.9994569420814514 ,D(G(z)) 2.5023288074846515\n",
      "epoch: 84 ,i: 500 ,Loss_D: 0.028961289674043655 ,Loss_G: 6.366488456726074 ,D(x): 0.9804657101631165 ,D(G(z)) 1.2712476027844901\n",
      "epoch: 84 ,i: 550 ,Loss_D: 0.13420839607715607 ,Loss_G: 4.787446022033691 ,D(x): 0.9243617653846741 ,D(G(z)) 0.8948814542351132\n",
      "epoch: 84 ,i: 600 ,Loss_D: 0.0905885249376297 ,Loss_G: 6.521858215332031 ,D(x): 0.9398096799850464 ,D(G(z)) 0.472736377787062\n",
      "epoch: 84 ,i: 650 ,Loss_D: 0.029057642444968224 ,Loss_G: 6.565363883972168 ,D(x): 0.9943474531173706 ,D(G(z)) 3.6311543894893723\n",
      "epoch: 84 ,i: 700 ,Loss_D: 0.010200729593634605 ,Loss_G: 6.806500434875488 ,D(x): 0.9929417371749878 ,D(G(z)) 0.7820017315848866\n",
      "epoch: 84 ,i: 750 ,Loss_D: 0.04940169304609299 ,Loss_G: 5.825821876525879 ,D(x): 0.9681272506713867 ,D(G(z)) 1.5841203267664894\n",
      "epoch: 85 ,i: 0 ,Loss_D: 0.3189699649810791 ,Loss_G: 13.038171768188477 ,D(x): 0.99946129322052 ,D(G(z)) 28946.219858790715\n",
      "epoch: 85 ,i: 50 ,Loss_D: 0.04044153168797493 ,Loss_G: 5.9236602783203125 ,D(x): 0.9798893928527832 ,D(G(z)) 1.701525088373902\n",
      "epoch: 85 ,i: 100 ,Loss_D: 0.007658217567950487 ,Loss_G: 7.148931980133057 ,D(x): 0.9994183778762817 ,D(G(z)) 1.9217647361577423\n",
      "epoch: 85 ,i: 150 ,Loss_D: 0.007355144247412682 ,Loss_G: 7.878998756408691 ,D(x): 0.9963704943656921 ,D(G(z)) 1.8840674659104235\n",
      "epoch: 85 ,i: 200 ,Loss_D: 0.008282601833343506 ,Loss_G: 6.85368537902832 ,D(x): 0.9982728958129883 ,D(G(z)) 1.609069194537468\n",
      "epoch: 85 ,i: 250 ,Loss_D: 0.03691268339753151 ,Loss_G: 9.527286529541016 ,D(x): 0.9661999940872192 ,D(G(z)) 1.099920026822077\n",
      "epoch: 85 ,i: 300 ,Loss_D: 0.10254836827516556 ,Loss_G: 5.50180721282959 ,D(x): 0.989620566368103 ,D(G(z)) 6.935242787136971\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 85 ,i: 350 ,Loss_D: 0.03187693655490875 ,Loss_G: 6.757904529571533 ,D(x): 0.9910227060317993 ,D(G(z)) 4.765537325858428\n",
      "epoch: 85 ,i: 400 ,Loss_D: 0.04737471789121628 ,Loss_G: 6.056509971618652 ,D(x): 0.9735618829727173 ,D(G(z)) 1.7004557275457506\n",
      "epoch: 85 ,i: 450 ,Loss_D: 0.02453528717160225 ,Loss_G: 6.634005069732666 ,D(x): 0.9928160905838013 ,D(G(z)) 3.0369376466853923\n",
      "epoch: 85 ,i: 500 ,Loss_D: 0.050218723714351654 ,Loss_G: 6.199556827545166 ,D(x): 0.9576363563537598 ,D(G(z)) 0.22181349147569596\n",
      "epoch: 85 ,i: 550 ,Loss_D: 0.039202965795993805 ,Loss_G: 5.86899471282959 ,D(x): 0.9870527386665344 ,D(G(z)) 2.887858317611628\n",
      "epoch: 85 ,i: 600 ,Loss_D: 0.28154611587524414 ,Loss_G: 9.831233024597168 ,D(x): 0.9891841411590576 ,D(G(z)) 1005.181751469299\n",
      "epoch: 85 ,i: 650 ,Loss_D: 0.18743380904197693 ,Loss_G: 3.2957708835601807 ,D(x): 0.8651963472366333 ,D(G(z)) 0.017682823675129335\n",
      "epoch: 85 ,i: 700 ,Loss_D: 0.15168313682079315 ,Loss_G: 4.652369976043701 ,D(x): 0.9022839665412903 ,D(G(z)) 0.2051692029477531\n",
      "epoch: 85 ,i: 750 ,Loss_D: 0.025966856628656387 ,Loss_G: 5.15478515625 ,D(x): 0.9939927458763123 ,D(G(z)) 0.4727756820255781\n",
      "epoch: 86 ,i: 0 ,Loss_D: 0.011001663282513618 ,Loss_G: 6.998626708984375 ,D(x): 0.9955159425735474 ,D(G(z)) 1.7913792779873319\n",
      "epoch: 86 ,i: 50 ,Loss_D: 0.6357304453849792 ,Loss_G: 9.075672149658203 ,D(x): 0.988154411315918 ,D(G(z)) 939.5154165807704\n",
      "epoch: 86 ,i: 100 ,Loss_D: 0.2046472281217575 ,Loss_G: 9.999408721923828 ,D(x): 0.9978294372558594 ,D(G(z)) 1310.2976215320246\n",
      "epoch: 86 ,i: 150 ,Loss_D: 0.06608927249908447 ,Loss_G: 5.967116355895996 ,D(x): 0.9541230201721191 ,D(G(z)) 0.9804010385763952\n",
      "epoch: 86 ,i: 200 ,Loss_D: 0.0883202850818634 ,Loss_G: 6.465980529785156 ,D(x): 0.9352840185165405 ,D(G(z)) 0.9571870726710735\n",
      "epoch: 86 ,i: 250 ,Loss_D: 0.0214640311896801 ,Loss_G: 6.506166458129883 ,D(x): 0.9924530982971191 ,D(G(z)) 2.4090775278338636\n",
      "epoch: 86 ,i: 300 ,Loss_D: 0.023324675858020782 ,Loss_G: 6.6413140296936035 ,D(x): 0.9820632934570312 ,D(G(z)) 0.8270773989553486\n",
      "epoch: 86 ,i: 350 ,Loss_D: 0.4937892556190491 ,Loss_G: 3.249199390411377 ,D(x): 0.864802360534668 ,D(G(z)) 2.5340123675546224\n",
      "epoch: 86 ,i: 400 ,Loss_D: 0.36658021807670593 ,Loss_G: 10.727690696716309 ,D(x): 0.9980511665344238 ,D(G(z)) 3602.952757762696\n",
      "epoch: 86 ,i: 450 ,Loss_D: 0.03875317797064781 ,Loss_G: 6.8912177085876465 ,D(x): 0.9947666525840759 ,D(G(z)) 7.903394569392044\n",
      "epoch: 86 ,i: 500 ,Loss_D: 0.03340284526348114 ,Loss_G: 5.073275566101074 ,D(x): 0.9943817853927612 ,D(G(z)) 0.7893622648623467\n",
      "epoch: 86 ,i: 550 ,Loss_D: 0.04452585428953171 ,Loss_G: 5.765956878662109 ,D(x): 0.9650131464004517 ,D(G(z)) 0.45244039949610515\n",
      "epoch: 86 ,i: 600 ,Loss_D: 0.05023922771215439 ,Loss_G: 6.788596153259277 ,D(x): 0.9634002447128296 ,D(G(z)) 1.470723514942757\n",
      "epoch: 86 ,i: 650 ,Loss_D: 0.09407031536102295 ,Loss_G: 5.343398094177246 ,D(x): 0.928246259689331 ,D(G(z)) 0.20876793847239078\n",
      "epoch: 86 ,i: 700 ,Loss_D: 0.09717363864183426 ,Loss_G: 5.43936824798584 ,D(x): 0.922009289264679 ,D(G(z)) 0.12056566594555737\n",
      "epoch: 86 ,i: 750 ,Loss_D: 0.07400944828987122 ,Loss_G: 5.303363800048828 ,D(x): 0.9431615471839905 ,D(G(z)) 0.48601689763727723\n",
      "epoch: 87 ,i: 0 ,Loss_D: 0.009156780317425728 ,Loss_G: 6.886046886444092 ,D(x): 0.9976150989532471 ,D(G(z)) 1.0685461688108462\n",
      "epoch: 87 ,i: 50 ,Loss_D: 0.04675145819783211 ,Loss_G: 7.774194717407227 ,D(x): 0.9978611469268799 ,D(G(z)) 22.397065929059632\n",
      "epoch: 87 ,i: 100 ,Loss_D: 0.04193228483200073 ,Loss_G: 6.115418434143066 ,D(x): 0.9890449047088623 ,D(G(z)) 4.412187329933069\n",
      "epoch: 87 ,i: 150 ,Loss_D: 0.0462777353823185 ,Loss_G: 5.208563804626465 ,D(x): 0.9629859328269958 ,D(G(z)) 0.3049884930796409\n",
      "epoch: 87 ,i: 200 ,Loss_D: 0.08312606811523438 ,Loss_G: 4.886980056762695 ,D(x): 0.9625769853591919 ,D(G(z)) 1.6140072786402755\n",
      "epoch: 87 ,i: 250 ,Loss_D: 0.028698040172457695 ,Loss_G: 8.527230262756348 ,D(x): 0.9894484281539917 ,D(G(z)) 8.506097880066067\n",
      "epoch: 87 ,i: 300 ,Loss_D: 0.09062527120113373 ,Loss_G: 7.221356391906738 ,D(x): 0.9797278642654419 ,D(G(z)) 21.23791373250461\n",
      "epoch: 87 ,i: 350 ,Loss_D: 0.2610165476799011 ,Loss_G: 5.109363555908203 ,D(x): 0.9919936656951904 ,D(G(z)) 9.786651244488434\n",
      "epoch: 87 ,i: 400 ,Loss_D: 0.029865074902772903 ,Loss_G: 6.847793102264404 ,D(x): 0.9793883562088013 ,D(G(z)) 1.0479807325292947\n",
      "epoch: 87 ,i: 450 ,Loss_D: 0.10916014015674591 ,Loss_G: 4.861485004425049 ,D(x): 0.9399851560592651 ,D(G(z)) 0.9863416050508015\n",
      "epoch: 87 ,i: 500 ,Loss_D: 0.020115884020924568 ,Loss_G: 7.069802284240723 ,D(x): 0.9845758080482483 ,D(G(z)) 1.046696074091451\n",
      "epoch: 87 ,i: 550 ,Loss_D: 0.0722573772072792 ,Loss_G: 6.112738609313965 ,D(x): 0.9406459331512451 ,D(G(z)) 0.14342870491266446\n",
      "epoch: 87 ,i: 600 ,Loss_D: 0.036284495145082474 ,Loss_G: 6.5179338455200195 ,D(x): 0.9963840842247009 ,D(G(z)) 7.650124581878534\n",
      "epoch: 87 ,i: 650 ,Loss_D: 0.05401062220335007 ,Loss_G: 6.06915807723999 ,D(x): 0.9684528112411499 ,D(G(z)) 0.8571992812270309\n",
      "epoch: 87 ,i: 700 ,Loss_D: 0.0804322138428688 ,Loss_G: 8.651969909667969 ,D(x): 0.9955861568450928 ,D(G(z)) 153.7498444679877\n",
      "epoch: 87 ,i: 750 ,Loss_D: 0.06225426867604256 ,Loss_G: 8.001631736755371 ,D(x): 0.9934673309326172 ,D(G(z)) 18.887406455187396\n",
      "epoch: 88 ,i: 0 ,Loss_D: 0.42479076981544495 ,Loss_G: 8.709863662719727 ,D(x): 0.9779589176177979 ,D(G(z)) 568.7266396739775\n",
      "epoch: 88 ,i: 50 ,Loss_D: 0.030688729137182236 ,Loss_G: 6.889504432678223 ,D(x): 0.9861131906509399 ,D(G(z)) 3.7369335305334594\n",
      "epoch: 88 ,i: 100 ,Loss_D: 0.02767849899828434 ,Loss_G: 6.490877151489258 ,D(x): 0.9824507236480713 ,D(G(z)) 1.40947756090281\n",
      "epoch: 88 ,i: 150 ,Loss_D: 0.11394569277763367 ,Loss_G: 4.89749813079834 ,D(x): 0.9177457094192505 ,D(G(z)) 0.2011864572419148\n",
      "epoch: 88 ,i: 200 ,Loss_D: 0.143137127161026 ,Loss_G: 6.797504425048828 ,D(x): 0.979310929775238 ,D(G(z)) 23.482593064412285\n",
      "epoch: 88 ,i: 250 ,Loss_D: 0.08731644600629807 ,Loss_G: 5.3941802978515625 ,D(x): 0.9814725518226624 ,D(G(z)) 2.758328410295946\n",
      "epoch: 88 ,i: 300 ,Loss_D: 0.03541235253214836 ,Loss_G: 5.691751480102539 ,D(x): 0.9762170910835266 ,D(G(z)) 0.740130108641532\n",
      "epoch: 88 ,i: 350 ,Loss_D: 0.12719032168388367 ,Loss_G: 5.62297248840332 ,D(x): 0.9405547976493835 ,D(G(z)) 0.18828621149111124\n",
      "epoch: 88 ,i: 400 ,Loss_D: 0.10790136456489563 ,Loss_G: 6.007536888122559 ,D(x): 0.935832142829895 ,D(G(z)) 2.4011234590736255\n",
      "epoch: 88 ,i: 450 ,Loss_D: 0.06187105178833008 ,Loss_G: 4.367254257202148 ,D(x): 0.9596108198165894 ,D(G(z)) 0.4721515110506485\n",
      "epoch: 88 ,i: 500 ,Loss_D: 0.029922794550657272 ,Loss_G: 6.494281768798828 ,D(x): 0.9948183298110962 ,D(G(z)) 4.73183037959594\n",
      "epoch: 88 ,i: 550 ,Loss_D: 0.0765361413359642 ,Loss_G: 7.926205158233643 ,D(x): 0.9916895627975464 ,D(G(z)) 54.18507353574745\n",
      "epoch: 88 ,i: 600 ,Loss_D: 0.04934627562761307 ,Loss_G: 7.595108509063721 ,D(x): 0.9985866546630859 ,D(G(z)) 30.19589499172095\n",
      "epoch: 88 ,i: 650 ,Loss_D: 0.02815859019756317 ,Loss_G: 6.920810699462891 ,D(x): 0.9949077367782593 ,D(G(z)) 5.45227881745705\n",
      "epoch: 88 ,i: 700 ,Loss_D: 0.009154429659247398 ,Loss_G: 7.203010559082031 ,D(x): 0.9938996434211731 ,D(G(z)) 0.6858536757436293\n",
      "epoch: 88 ,i: 750 ,Loss_D: 0.009816071949899197 ,Loss_G: 7.506962776184082 ,D(x): 0.9993011951446533 ,D(G(z)) 3.031648852746883\n",
      "epoch: 89 ,i: 0 ,Loss_D: 0.009849375113844872 ,Loss_G: 6.858580589294434 ,D(x): 0.9981059432029724 ,D(G(z)) 2.029364470449385\n",
      "epoch: 89 ,i: 50 ,Loss_D: 0.027326274663209915 ,Loss_G: 7.120395660400391 ,D(x): 0.9826298952102661 ,D(G(z)) 2.244396172617889\n",
      "epoch: 89 ,i: 100 ,Loss_D: 0.009304920211434364 ,Loss_G: 7.542352676391602 ,D(x): 0.9934791922569275 ,D(G(z)) 1.5918206586345736\n",
      "epoch: 89 ,i: 150 ,Loss_D: 0.01017837505787611 ,Loss_G: 7.54233980178833 ,D(x): 0.9978761076927185 ,D(G(z)) 2.3905595088446625\n",
      "epoch: 89 ,i: 200 ,Loss_D: 0.7156115174293518 ,Loss_G: 11.423033714294434 ,D(x): 0.9983972907066345 ,D(G(z)) 7407.766058473919\n",
      "epoch: 89 ,i: 250 ,Loss_D: 0.06895472854375839 ,Loss_G: 7.187632083892822 ,D(x): 0.9977648258209229 ,D(G(z)) 19.691846281871975\n",
      "epoch: 89 ,i: 300 ,Loss_D: 0.08681336045265198 ,Loss_G: 5.076599597930908 ,D(x): 0.9368635416030884 ,D(G(z)) 0.3259424274838834\n",
      "epoch: 89 ,i: 350 ,Loss_D: 0.39587825536727905 ,Loss_G: 2.176823139190674 ,D(x): 0.8601334095001221 ,D(G(z)) 0.6032275162319555\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 89 ,i: 400 ,Loss_D: 0.07312756776809692 ,Loss_G: 7.312808990478516 ,D(x): 0.9930278062820435 ,D(G(z)) 14.155308871107493\n",
      "epoch: 89 ,i: 450 ,Loss_D: 0.16113117337226868 ,Loss_G: 6.853011131286621 ,D(x): 0.9712828397750854 ,D(G(z)) 13.455910845283954\n",
      "epoch: 89 ,i: 500 ,Loss_D: 0.04896427318453789 ,Loss_G: 6.267934322357178 ,D(x): 0.9834452867507935 ,D(G(z)) 3.7010878422233127\n",
      "epoch: 89 ,i: 550 ,Loss_D: 0.2668342888355255 ,Loss_G: 4.214542388916016 ,D(x): 0.8299425840377808 ,D(G(z)) 0.39769600780986875\n",
      "epoch: 89 ,i: 600 ,Loss_D: 0.008747805841267109 ,Loss_G: 6.842343330383301 ,D(x): 0.9938145875930786 ,D(G(z)) 0.5713407833919437\n",
      "epoch: 89 ,i: 650 ,Loss_D: 0.06909698992967606 ,Loss_G: 4.613466262817383 ,D(x): 0.948411762714386 ,D(G(z)) 0.17772002429798958\n",
      "epoch: 89 ,i: 700 ,Loss_D: 0.22011920809745789 ,Loss_G: 5.579555034637451 ,D(x): 0.9316903948783875 ,D(G(z)) 10.296063746725087\n",
      "epoch: 89 ,i: 750 ,Loss_D: 0.05514088645577431 ,Loss_G: 6.373716831207275 ,D(x): 0.9619442224502563 ,D(G(z)) 1.822385154460909\n",
      "epoch: 90 ,i: 0 ,Loss_D: 7.261612892150879 ,Loss_G: 13.208621978759766 ,D(x): 0.9999970197677612 ,D(G(z)) 9908.926207228073\n",
      "epoch: 90 ,i: 50 ,Loss_D: 0.07260581851005554 ,Loss_G: 6.531242370605469 ,D(x): 0.965499222278595 ,D(G(z)) 4.325995343332327\n",
      "epoch: 90 ,i: 100 ,Loss_D: 0.08306117355823517 ,Loss_G: 4.638119697570801 ,D(x): 0.9362066388130188 ,D(G(z)) 0.24761240563432543\n",
      "epoch: 90 ,i: 150 ,Loss_D: 0.06472406536340714 ,Loss_G: 6.946271896362305 ,D(x): 0.9923733472824097 ,D(G(z)) 14.415377271721793\n",
      "epoch: 90 ,i: 200 ,Loss_D: 0.04256276413798332 ,Loss_G: 5.03153133392334 ,D(x): 0.9700335264205933 ,D(G(z)) 0.5003380513634058\n",
      "epoch: 90 ,i: 250 ,Loss_D: 0.20211070775985718 ,Loss_G: 5.7825164794921875 ,D(x): 0.8842659592628479 ,D(G(z)) 0.2565749647478683\n",
      "epoch: 90 ,i: 300 ,Loss_D: 0.011001783423125744 ,Loss_G: 6.803167819976807 ,D(x): 0.9964308738708496 ,D(G(z)) 1.3585701672054296\n",
      "epoch: 90 ,i: 350 ,Loss_D: 0.011152936145663261 ,Loss_G: 7.142956256866455 ,D(x): 0.9957583546638489 ,D(G(z)) 2.059559820858422\n",
      "epoch: 90 ,i: 400 ,Loss_D: 0.22112634778022766 ,Loss_G: 6.444901466369629 ,D(x): 0.9963971972465515 ,D(G(z)) 34.4983537351164\n",
      "epoch: 90 ,i: 450 ,Loss_D: 0.31108078360557556 ,Loss_G: 3.635161876678467 ,D(x): 0.8533738255500793 ,D(G(z)) 1.3889682701446124\n",
      "epoch: 90 ,i: 500 ,Loss_D: 0.0544305220246315 ,Loss_G: 6.316139221191406 ,D(x): 0.966010570526123 ,D(G(z)) 1.3007980981390346\n",
      "epoch: 90 ,i: 550 ,Loss_D: 0.038306888192892075 ,Loss_G: 6.789865493774414 ,D(x): 0.9847890734672546 ,D(G(z)) 5.102258335305062\n",
      "epoch: 90 ,i: 600 ,Loss_D: 0.06716781854629517 ,Loss_G: 6.141570091247559 ,D(x): 0.951962947845459 ,D(G(z)) 0.7611027978346019\n",
      "epoch: 90 ,i: 650 ,Loss_D: 0.020544592291116714 ,Loss_G: 5.269200325012207 ,D(x): 0.994796872138977 ,D(G(z)) 1.1460206756762725\n",
      "epoch: 90 ,i: 700 ,Loss_D: 0.8597865104675293 ,Loss_G: 7.309920310974121 ,D(x): 0.988129734992981 ,D(G(z)) 294.5004737557188\n",
      "epoch: 90 ,i: 750 ,Loss_D: 0.057400524616241455 ,Loss_G: 6.244328498840332 ,D(x): 0.9839631915092468 ,D(G(z)) 5.169841543325772\n",
      "epoch: 91 ,i: 0 ,Loss_D: 0.01597668044269085 ,Loss_G: 6.456575393676758 ,D(x): 0.9960381388664246 ,D(G(z)) 1.7606043133770661\n",
      "epoch: 91 ,i: 50 ,Loss_D: 0.0401027575135231 ,Loss_G: 6.231827735900879 ,D(x): 0.9923527240753174 ,D(G(z)) 4.998789298036731\n",
      "epoch: 91 ,i: 100 ,Loss_D: 0.044013842940330505 ,Loss_G: 5.604189395904541 ,D(x): 0.9736911654472351 ,D(G(z)) 0.9201791441046602\n",
      "epoch: 91 ,i: 150 ,Loss_D: 0.0711672455072403 ,Loss_G: 5.597314357757568 ,D(x): 0.9408865571022034 ,D(G(z)) 0.23571172672013677\n",
      "epoch: 91 ,i: 200 ,Loss_D: 0.029204899445176125 ,Loss_G: 5.702140808105469 ,D(x): 0.9843524694442749 ,D(G(z)) 1.2685285505983275\n",
      "epoch: 91 ,i: 250 ,Loss_D: 0.08669599890708923 ,Loss_G: 6.047579765319824 ,D(x): 0.9408421516418457 ,D(G(z)) 1.391660562374849\n",
      "epoch: 91 ,i: 300 ,Loss_D: 0.017340796068310738 ,Loss_G: 7.016839027404785 ,D(x): 0.9949927926063538 ,D(G(z)) 2.9522315175052674\n",
      "epoch: 91 ,i: 350 ,Loss_D: 0.17151200771331787 ,Loss_G: 5.94064474105835 ,D(x): 0.9446976780891418 ,D(G(z)) 13.975512937243854\n",
      "epoch: 91 ,i: 400 ,Loss_D: 0.07509155571460724 ,Loss_G: 6.663348197937012 ,D(x): 0.9954941272735596 ,D(G(z)) 13.226416521863868\n",
      "epoch: 91 ,i: 450 ,Loss_D: 0.0828089714050293 ,Loss_G: 5.238254547119141 ,D(x): 0.9617642164230347 ,D(G(z)) 2.219115474386404\n",
      "epoch: 91 ,i: 500 ,Loss_D: 0.055455345660448074 ,Loss_G: 6.0229949951171875 ,D(x): 0.9622896909713745 ,D(G(z)) 1.2983653593402629\n",
      "epoch: 91 ,i: 550 ,Loss_D: 0.07032215595245361 ,Loss_G: 5.971031188964844 ,D(x): 0.9747765064239502 ,D(G(z)) 4.461121460471617\n",
      "epoch: 91 ,i: 600 ,Loss_D: 0.045007381588220596 ,Loss_G: 6.237414360046387 ,D(x): 0.9973440170288086 ,D(G(z)) 7.500330991240043\n",
      "epoch: 91 ,i: 650 ,Loss_D: 0.32781317830085754 ,Loss_G: 2.9801459312438965 ,D(x): 0.7941218018531799 ,D(G(z)) 0.23512417399364702\n",
      "epoch: 91 ,i: 700 ,Loss_D: 0.03414931148290634 ,Loss_G: 5.934597015380859 ,D(x): 0.979289174079895 ,D(G(z)) 1.6298133932225904\n",
      "epoch: 91 ,i: 750 ,Loss_D: 0.0339326485991478 ,Loss_G: 5.939554214477539 ,D(x): 0.9895754456520081 ,D(G(z)) 2.2799093435148152\n",
      "epoch: 92 ,i: 0 ,Loss_D: 0.02925814501941204 ,Loss_G: 6.586114406585693 ,D(x): 0.9991921186447144 ,D(G(z)) 5.803144324560055\n",
      "epoch: 92 ,i: 50 ,Loss_D: 0.10879764705896378 ,Loss_G: 5.862024784088135 ,D(x): 0.9354422092437744 ,D(G(z)) 1.4530360825298303\n",
      "epoch: 92 ,i: 100 ,Loss_D: 0.08620870113372803 ,Loss_G: 7.712466239929199 ,D(x): 0.9979504346847534 ,D(G(z)) 37.271772815579865\n",
      "epoch: 92 ,i: 150 ,Loss_D: 0.04313382878899574 ,Loss_G: 5.856511116027832 ,D(x): 0.9672866463661194 ,D(G(z)) 0.5906763203924633\n",
      "epoch: 92 ,i: 200 ,Loss_D: 0.003986545838415623 ,Loss_G: 7.624195098876953 ,D(x): 0.9981721639633179 ,D(G(z)) 0.9244253338264122\n",
      "epoch: 92 ,i: 250 ,Loss_D: 0.13969135284423828 ,Loss_G: 2.082104444503784 ,D(x): 0.8883939385414124 ,D(G(z)) 0.014429847795514029\n",
      "epoch: 92 ,i: 300 ,Loss_D: 1.8301340341567993 ,Loss_G: 12.789576530456543 ,D(x): 0.9998639822006226 ,D(G(z)) 7934.967664001652\n",
      "epoch: 92 ,i: 350 ,Loss_D: 0.729770302772522 ,Loss_G: 0.7394058108329773 ,D(x): 0.6099884510040283 ,D(G(z)) 0.001827724911274711\n",
      "epoch: 92 ,i: 400 ,Loss_D: 0.057042695581912994 ,Loss_G: 7.214341163635254 ,D(x): 0.9858976602554321 ,D(G(z)) 9.03528891637115\n",
      "epoch: 92 ,i: 450 ,Loss_D: 0.017741018906235695 ,Loss_G: 7.936031341552734 ,D(x): 0.991567850112915 ,D(G(z)) 3.6893678438410125\n",
      "epoch: 92 ,i: 500 ,Loss_D: 0.010750054381787777 ,Loss_G: 7.177604675292969 ,D(x): 0.9993435144424438 ,D(G(z)) 2.7729629627674988\n",
      "epoch: 92 ,i: 550 ,Loss_D: 0.015094881877303123 ,Loss_G: 6.11608362197876 ,D(x): 0.999661922454834 ,D(G(z)) 1.790769275852602\n",
      "epoch: 92 ,i: 600 ,Loss_D: 0.027701620012521744 ,Loss_G: 6.861391067504883 ,D(x): 0.9979055523872375 ,D(G(z)) 5.8866967498455\n",
      "epoch: 92 ,i: 650 ,Loss_D: 0.0033383765257894993 ,Loss_G: 9.008947372436523 ,D(x): 0.9975866675376892 ,D(G(z)) 1.9533979364631355\n",
      "epoch: 92 ,i: 700 ,Loss_D: 0.010666277259588242 ,Loss_G: 8.02569580078125 ,D(x): 0.9926507472991943 ,D(G(z)) 1.3353429240406982\n",
      "epoch: 92 ,i: 750 ,Loss_D: 0.035506244748830795 ,Loss_G: 5.822277545928955 ,D(x): 0.9797192811965942 ,D(G(z)) 0.7055929849688529\n",
      "epoch: 93 ,i: 0 ,Loss_D: 0.09369224309921265 ,Loss_G: 4.40665340423584 ,D(x): 0.9439465999603271 ,D(G(z)) 0.8824697335080621\n",
      "epoch: 93 ,i: 50 ,Loss_D: 0.08874784409999847 ,Loss_G: 6.443865776062012 ,D(x): 0.9659000635147095 ,D(G(z)) 5.052096905136515\n",
      "epoch: 93 ,i: 100 ,Loss_D: 0.06264108419418335 ,Loss_G: 5.175106048583984 ,D(x): 0.9537345170974731 ,D(G(z)) 0.5614070043421803\n",
      "epoch: 93 ,i: 150 ,Loss_D: 0.06118061766028404 ,Loss_G: 6.54593563079834 ,D(x): 0.9984269738197327 ,D(G(z)) 11.313936895544632\n",
      "epoch: 93 ,i: 200 ,Loss_D: 0.012135216034948826 ,Loss_G: 7.445965766906738 ,D(x): 0.9967443943023682 ,D(G(z)) 3.2365376656915665\n",
      "epoch: 93 ,i: 250 ,Loss_D: 0.03366470709443092 ,Loss_G: 6.355186462402344 ,D(x): 0.9992684125900269 ,D(G(z)) 6.347687846151872\n",
      "epoch: 93 ,i: 300 ,Loss_D: 0.06788188964128494 ,Loss_G: 8.45106029510498 ,D(x): 0.9399881362915039 ,D(G(z)) 0.375262693397173\n",
      "epoch: 93 ,i: 350 ,Loss_D: 0.23233070969581604 ,Loss_G: 13.655799865722656 ,D(x): 0.997137725353241 ,D(G(z)) 34271.92153625\n",
      "epoch: 93 ,i: 400 ,Loss_D: 0.11926469206809998 ,Loss_G: 7.55438756942749 ,D(x): 0.9209784865379333 ,D(G(z)) 3.035861794307713\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 93 ,i: 450 ,Loss_D: 0.12548649311065674 ,Loss_G: 5.789559364318848 ,D(x): 0.9465630054473877 ,D(G(z)) 4.494892081014152\n",
      "epoch: 93 ,i: 500 ,Loss_D: 0.0268878024071455 ,Loss_G: 7.744402885437012 ,D(x): 0.9813072681427002 ,D(G(z)) 4.032379656844411\n",
      "epoch: 93 ,i: 550 ,Loss_D: 0.016895022243261337 ,Loss_G: 6.78704833984375 ,D(x): 0.9935556054115295 ,D(G(z)) 2.2534145860277515\n",
      "epoch: 93 ,i: 600 ,Loss_D: 0.05953935533761978 ,Loss_G: 7.532644748687744 ,D(x): 0.9997274875640869 ,D(G(z)) 37.596197248418214\n",
      "epoch: 93 ,i: 650 ,Loss_D: 0.14122581481933594 ,Loss_G: 6.765284061431885 ,D(x): 0.9984415173530579 ,D(G(z)) 34.87231153821426\n",
      "epoch: 93 ,i: 700 ,Loss_D: 0.04533066600561142 ,Loss_G: 6.371410846710205 ,D(x): 0.9910848736763 ,D(G(z)) 4.1619102734962965\n",
      "epoch: 93 ,i: 750 ,Loss_D: 0.1166875958442688 ,Loss_G: 7.838974952697754 ,D(x): 0.9980289936065674 ,D(G(z)) 87.99380164973321\n",
      "epoch: 94 ,i: 0 ,Loss_D: 0.015160919167101383 ,Loss_G: 7.153446197509766 ,D(x): 0.9950758814811707 ,D(G(z)) 2.3280592751831373\n",
      "epoch: 94 ,i: 50 ,Loss_D: 0.19037172198295593 ,Loss_G: 5.219217300415039 ,D(x): 0.9473237991333008 ,D(G(z)) 3.8150582126358388\n",
      "epoch: 94 ,i: 100 ,Loss_D: 0.019898071885108948 ,Loss_G: 6.922108173370361 ,D(x): 0.9952893853187561 ,D(G(z)) 3.2928122115036014\n",
      "epoch: 94 ,i: 150 ,Loss_D: 0.08528725057840347 ,Loss_G: 7.045041561126709 ,D(x): 0.9961706399917603 ,D(G(z)) 26.611868671158497\n",
      "epoch: 94 ,i: 200 ,Loss_D: 2.670187473297119 ,Loss_G: 12.852544784545898 ,D(x): 0.9999665021896362 ,D(G(z)) 21941.342615920876\n",
      "epoch: 94 ,i: 250 ,Loss_D: 0.03346092253923416 ,Loss_G: 7.119325637817383 ,D(x): 0.9910682439804077 ,D(G(z)) 5.647672795248251\n",
      "epoch: 94 ,i: 300 ,Loss_D: 0.19280734658241272 ,Loss_G: 8.935171127319336 ,D(x): 0.995791494846344 ,D(G(z)) 454.82877215019516\n",
      "epoch: 94 ,i: 350 ,Loss_D: 0.24091914296150208 ,Loss_G: 4.9152984619140625 ,D(x): 0.8868396282196045 ,D(G(z)) 2.6479018872403324\n",
      "epoch: 94 ,i: 400 ,Loss_D: 0.13883812725543976 ,Loss_G: 5.005598545074463 ,D(x): 0.8950793743133545 ,D(G(z)) 0.2089825086909824\n",
      "epoch: 94 ,i: 450 ,Loss_D: 0.056758761405944824 ,Loss_G: 6.362198829650879 ,D(x): 0.9769418239593506 ,D(G(z)) 4.997680684952447\n",
      "epoch: 94 ,i: 500 ,Loss_D: 6.393938064575195 ,Loss_G: 2.4048023223876953 ,D(x): 0.011671984568238258 ,D(G(z)) 2.8863889414768365e-05\n",
      "epoch: 94 ,i: 550 ,Loss_D: 0.09908567368984222 ,Loss_G: 6.40838623046875 ,D(x): 0.9904861450195312 ,D(G(z)) 14.968884694773188\n",
      "epoch: 94 ,i: 600 ,Loss_D: 0.031278785318136215 ,Loss_G: 6.062851905822754 ,D(x): 0.9825373888015747 ,D(G(z)) 0.9906419538097855\n",
      "epoch: 94 ,i: 650 ,Loss_D: 0.016123559325933456 ,Loss_G: 6.582850456237793 ,D(x): 0.994756281375885 ,D(G(z)) 1.6699408685076786\n",
      "epoch: 94 ,i: 700 ,Loss_D: 0.8697537779808044 ,Loss_G: 2.9228408336639404 ,D(x): 0.606842041015625 ,D(G(z)) 0.0002448588257365009\n",
      "epoch: 94 ,i: 750 ,Loss_D: 0.013531899079680443 ,Loss_G: 7.875840187072754 ,D(x): 0.9907433390617371 ,D(G(z)) 1.4202952728889973\n",
      "epoch: 95 ,i: 0 ,Loss_D: 2.118161916732788 ,Loss_G: 17.041166305541992 ,D(x): 0.9999770522117615 ,D(G(z)) 1969039.4165219914\n",
      "epoch: 95 ,i: 50 ,Loss_D: 0.0491635836660862 ,Loss_G: 6.12712287902832 ,D(x): 0.9763671159744263 ,D(G(z)) 2.938648423983215\n",
      "epoch: 95 ,i: 100 ,Loss_D: 0.11996697634458542 ,Loss_G: 5.746264457702637 ,D(x): 0.9276993274688721 ,D(G(z)) 1.4538218153126623\n",
      "epoch: 95 ,i: 150 ,Loss_D: 0.05989391729235649 ,Loss_G: 6.4786882400512695 ,D(x): 0.9828394651412964 ,D(G(z)) 5.810987127144239\n",
      "epoch: 95 ,i: 200 ,Loss_D: 0.08234046399593353 ,Loss_G: 5.188929080963135 ,D(x): 0.9540457129478455 ,D(G(z)) 1.6377033443223639\n",
      "epoch: 95 ,i: 250 ,Loss_D: 0.016518743708729744 ,Loss_G: 7.115205764770508 ,D(x): 0.9871123433113098 ,D(G(z)) 1.000403758459059\n",
      "epoch: 95 ,i: 300 ,Loss_D: 0.027395956218242645 ,Loss_G: 6.928698539733887 ,D(x): 0.9941298961639404 ,D(G(z)) 5.307225264054996\n",
      "epoch: 95 ,i: 350 ,Loss_D: 0.01711254194378853 ,Loss_G: 6.341071128845215 ,D(x): 0.9876374006271362 ,D(G(z)) 0.5821304973021668\n",
      "epoch: 95 ,i: 400 ,Loss_D: 0.022217409685254097 ,Loss_G: 7.630263328552246 ,D(x): 0.9988133907318115 ,D(G(z)) 7.508359481630528\n",
      "epoch: 95 ,i: 450 ,Loss_D: 0.04829852283000946 ,Loss_G: 7.726032733917236 ,D(x): 0.9558544158935547 ,D(G(z)) 0.3040699081375696\n",
      "epoch: 95 ,i: 500 ,Loss_D: 0.017654292285442352 ,Loss_G: 6.822431564331055 ,D(x): 0.986793041229248 ,D(G(z)) 1.1521065665991863\n",
      "epoch: 95 ,i: 550 ,Loss_D: 0.015239226631820202 ,Loss_G: 8.620626449584961 ,D(x): 0.9862607717514038 ,D(G(z)) 0.8146560392156613\n",
      "epoch: 95 ,i: 600 ,Loss_D: 0.025074003264307976 ,Loss_G: 5.254803657531738 ,D(x): 0.979966402053833 ,D(G(z)) 0.2628623919626533\n",
      "epoch: 95 ,i: 650 ,Loss_D: 0.08660431206226349 ,Loss_G: 6.724808216094971 ,D(x): 0.9800010919570923 ,D(G(z)) 11.877036945879992\n",
      "epoch: 95 ,i: 700 ,Loss_D: 0.03407345712184906 ,Loss_G: 7.347007751464844 ,D(x): 0.9859416484832764 ,D(G(z)) 6.316996683854397\n",
      "epoch: 95 ,i: 750 ,Loss_D: 0.04329333454370499 ,Loss_G: 6.4575042724609375 ,D(x): 0.978767991065979 ,D(G(z)) 4.540579237035703\n",
      "epoch: 96 ,i: 0 ,Loss_D: 0.21652035415172577 ,Loss_G: 6.379431247711182 ,D(x): 0.9832414388656616 ,D(G(z)) 22.910355743361237\n",
      "epoch: 96 ,i: 50 ,Loss_D: 0.06032881140708923 ,Loss_G: 6.069434642791748 ,D(x): 0.9484944939613342 ,D(G(z)) 0.4227676552500022\n",
      "epoch: 96 ,i: 100 ,Loss_D: 0.09450861066579819 ,Loss_G: 7.770868301391602 ,D(x): 0.9927025437355042 ,D(G(z)) 47.18371723403851\n",
      "epoch: 96 ,i: 150 ,Loss_D: 0.3034778833389282 ,Loss_G: 5.21207332611084 ,D(x): 0.930539071559906 ,D(G(z)) 12.604309208855081\n",
      "epoch: 96 ,i: 200 ,Loss_D: 0.09163232892751694 ,Loss_G: 5.938153266906738 ,D(x): 0.9303332567214966 ,D(G(z)) 0.31369508161958115\n",
      "epoch: 96 ,i: 250 ,Loss_D: 0.03441523760557175 ,Loss_G: 6.45032262802124 ,D(x): 0.9981213212013245 ,D(G(z)) 4.4050711239249525\n",
      "epoch: 96 ,i: 300 ,Loss_D: 0.03184958174824715 ,Loss_G: 6.470277786254883 ,D(x): 0.9774926900863647 ,D(G(z)) 1.192535188704386\n",
      "epoch: 96 ,i: 350 ,Loss_D: 0.06514573097229004 ,Loss_G: 7.80361795425415 ,D(x): 0.946791410446167 ,D(G(z)) 1.1803873314787074\n",
      "epoch: 96 ,i: 400 ,Loss_D: 0.015230882912874222 ,Loss_G: 7.302201271057129 ,D(x): 0.9991674423217773 ,D(G(z)) 3.735445325710983\n",
      "epoch: 96 ,i: 450 ,Loss_D: 0.02840219810605049 ,Loss_G: 6.469481468200684 ,D(x): 0.9753767251968384 ,D(G(z)) 0.38032701608913855\n",
      "epoch: 96 ,i: 500 ,Loss_D: 0.02748866379261017 ,Loss_G: 6.258318901062012 ,D(x): 0.9848469495773315 ,D(G(z)) 1.3039439393882561\n",
      "epoch: 96 ,i: 550 ,Loss_D: 0.033733297139406204 ,Loss_G: 4.669843673706055 ,D(x): 0.9920730590820312 ,D(G(z)) 0.3977248476328389\n",
      "epoch: 96 ,i: 600 ,Loss_D: 0.08175156265497208 ,Loss_G: 7.213497161865234 ,D(x): 0.9950494766235352 ,D(G(z)) 17.76061035384923\n",
      "epoch: 96 ,i: 650 ,Loss_D: 0.017077140510082245 ,Loss_G: 7.066864013671875 ,D(x): 0.9991685152053833 ,D(G(z)) 2.861727584653302\n",
      "epoch: 96 ,i: 700 ,Loss_D: 0.09858793020248413 ,Loss_G: 6.063778400421143 ,D(x): 0.9339523315429688 ,D(G(z)) 0.13105496428102537\n",
      "epoch: 96 ,i: 750 ,Loss_D: 0.20863328874111176 ,Loss_G: 5.954938888549805 ,D(x): 0.9677449464797974 ,D(G(z)) 18.30584434594089\n",
      "epoch: 97 ,i: 0 ,Loss_D: 0.2109958827495575 ,Loss_G: 7.652067184448242 ,D(x): 0.9949876070022583 ,D(G(z)) 162.5923687988301\n",
      "epoch: 97 ,i: 50 ,Loss_D: 0.05439961701631546 ,Loss_G: 6.757868766784668 ,D(x): 0.9721204042434692 ,D(G(z)) 4.326563243950294\n",
      "epoch: 97 ,i: 100 ,Loss_D: 0.08722089231014252 ,Loss_G: 6.639538764953613 ,D(x): 0.9922090768814087 ,D(G(z)) 21.332547594317887\n",
      "epoch: 97 ,i: 150 ,Loss_D: 0.04561188817024231 ,Loss_G: 7.123691558837891 ,D(x): 0.9933902621269226 ,D(G(z)) 9.569801975649206\n",
      "epoch: 97 ,i: 200 ,Loss_D: 0.08143054693937302 ,Loss_G: 6.913928985595703 ,D(x): 0.9865102767944336 ,D(G(z)) 12.532608966203172\n",
      "epoch: 97 ,i: 250 ,Loss_D: 0.021578583866357803 ,Loss_G: 7.095151901245117 ,D(x): 0.9952122569084167 ,D(G(z)) 4.126643208139426\n",
      "epoch: 97 ,i: 300 ,Loss_D: 0.030703561380505562 ,Loss_G: 6.265583038330078 ,D(x): 0.9783413410186768 ,D(G(z)) 0.8804476331225266\n",
      "epoch: 97 ,i: 350 ,Loss_D: 0.08729681372642517 ,Loss_G: 6.1903533935546875 ,D(x): 0.9969495534896851 ,D(G(z)) 10.14583539716355\n",
      "epoch: 97 ,i: 400 ,Loss_D: 0.017541544511914253 ,Loss_G: 6.449029922485352 ,D(x): 0.9966586828231812 ,D(G(z)) 2.8397309379317677\n",
      "epoch: 97 ,i: 450 ,Loss_D: 0.16025297343730927 ,Loss_G: 5.176727771759033 ,D(x): 0.8875617980957031 ,D(G(z)) 0.03178349165065314\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 97 ,i: 500 ,Loss_D: 0.04506218433380127 ,Loss_G: 6.365740776062012 ,D(x): 0.9740172624588013 ,D(G(z)) 1.872291701176999\n",
      "epoch: 97 ,i: 550 ,Loss_D: 0.03008173033595085 ,Loss_G: 6.3022871017456055 ,D(x): 0.9826827049255371 ,D(G(z)) 1.2840505151713932\n",
      "epoch: 97 ,i: 600 ,Loss_D: 0.011633966118097305 ,Loss_G: 8.088661193847656 ,D(x): 0.9931389093399048 ,D(G(z)) 1.6501208201099244\n",
      "epoch: 97 ,i: 650 ,Loss_D: 0.019867822527885437 ,Loss_G: 6.32070255279541 ,D(x): 0.996013879776001 ,D(G(z)) 1.8822873073310626\n",
      "epoch: 97 ,i: 700 ,Loss_D: 0.01896255649626255 ,Loss_G: 9.154142379760742 ,D(x): 0.991815984249115 ,D(G(z)) 21.111169654962982\n",
      "epoch: 97 ,i: 750 ,Loss_D: 0.01439591497182846 ,Loss_G: 7.054447174072266 ,D(x): 0.9940382242202759 ,D(G(z)) 2.151777609943491\n",
      "epoch: 98 ,i: 0 ,Loss_D: 0.010482851415872574 ,Loss_G: 7.700235366821289 ,D(x): 0.9942079782485962 ,D(G(z)) 1.8641099221403565\n",
      "epoch: 98 ,i: 50 ,Loss_D: 0.05400008708238602 ,Loss_G: 5.5510759353637695 ,D(x): 0.9605845212936401 ,D(G(z)) 0.5861878578977404\n",
      "epoch: 98 ,i: 100 ,Loss_D: 0.6315834522247314 ,Loss_G: 3.374234199523926 ,D(x): 0.7463182806968689 ,D(G(z)) 1.3201502490461827\n",
      "epoch: 98 ,i: 150 ,Loss_D: 0.199141263961792 ,Loss_G: 3.119847297668457 ,D(x): 0.9711877107620239 ,D(G(z)) 0.8394606996405256\n",
      "epoch: 98 ,i: 200 ,Loss_D: 0.10978183150291443 ,Loss_G: 6.354299545288086 ,D(x): 0.9933364391326904 ,D(G(z)) 14.509374441051188\n",
      "epoch: 98 ,i: 250 ,Loss_D: 0.11274343729019165 ,Loss_G: 6.795027732849121 ,D(x): 0.9752100706100464 ,D(G(z)) 12.260302485689285\n",
      "epoch: 98 ,i: 300 ,Loss_D: 0.536123514175415 ,Loss_G: 13.167278289794922 ,D(x): 0.9918828010559082 ,D(G(z)) 31447.25658846819\n",
      "epoch: 98 ,i: 350 ,Loss_D: 0.27994826436042786 ,Loss_G: 10.295650482177734 ,D(x): 0.9896864295005798 ,D(G(z)) 1488.7861315373893\n",
      "epoch: 98 ,i: 400 ,Loss_D: 0.026848824694752693 ,Loss_G: 6.184852600097656 ,D(x): 0.9877039194107056 ,D(G(z)) 1.6830951175662563\n",
      "epoch: 98 ,i: 450 ,Loss_D: 0.10550229251384735 ,Loss_G: 7.082819938659668 ,D(x): 0.9215583801269531 ,D(G(z)) 0.9546179798262081\n",
      "epoch: 98 ,i: 500 ,Loss_D: 0.051846280694007874 ,Loss_G: 7.380917549133301 ,D(x): 0.9534515738487244 ,D(G(z)) 0.7128950764203944\n",
      "epoch: 98 ,i: 550 ,Loss_D: 0.04133126139640808 ,Loss_G: 6.717540740966797 ,D(x): 0.9734793901443481 ,D(G(z)) 1.971121863534066\n",
      "epoch: 98 ,i: 600 ,Loss_D: 0.12214071303606033 ,Loss_G: 3.773634910583496 ,D(x): 0.9166017174720764 ,D(G(z)) 0.10068825443868705\n",
      "epoch: 98 ,i: 650 ,Loss_D: 0.20017264783382416 ,Loss_G: 8.3427734375 ,D(x): 0.9850035905838013 ,D(G(z)) 201.19077571308063\n",
      "epoch: 98 ,i: 700 ,Loss_D: 0.03160632774233818 ,Loss_G: 6.688243865966797 ,D(x): 0.9750230312347412 ,D(G(z)) 0.9987402071042295\n",
      "epoch: 98 ,i: 750 ,Loss_D: 0.029494404792785645 ,Loss_G: 7.174691200256348 ,D(x): 0.9927353858947754 ,D(G(z)) 4.721927541641315\n",
      "epoch: 99 ,i: 0 ,Loss_D: 0.019596118479967117 ,Loss_G: 7.47181510925293 ,D(x): 0.9908661842346191 ,D(G(z)) 3.1494233884657143\n",
      "epoch: 99 ,i: 50 ,Loss_D: 0.25321292877197266 ,Loss_G: 7.153507232666016 ,D(x): 0.9425541162490845 ,D(G(z)) 61.75979324895346\n",
      "epoch: 99 ,i: 100 ,Loss_D: 0.017568007111549377 ,Loss_G: 6.598134517669678 ,D(x): 0.9982320070266724 ,D(G(z)) 2.098474435363861\n",
      "epoch: 99 ,i: 150 ,Loss_D: 0.06692716479301453 ,Loss_G: 5.172484874725342 ,D(x): 0.9453447461128235 ,D(G(z)) 0.3091577134791556\n",
      "epoch: 99 ,i: 200 ,Loss_D: 0.34228819608688354 ,Loss_G: 4.817134857177734 ,D(x): 0.8621300458908081 ,D(G(z)) 3.7243365900761796\n",
      "epoch: 99 ,i: 250 ,Loss_D: 0.23922142386436462 ,Loss_G: 5.334869384765625 ,D(x): 0.9286200404167175 ,D(G(z)) 10.054961533944704\n",
      "epoch: 99 ,i: 300 ,Loss_D: 0.02576581761240959 ,Loss_G: 6.735494613647461 ,D(x): 0.9953036308288574 ,D(G(z)) 4.933828528812781\n",
      "epoch: 99 ,i: 350 ,Loss_D: 0.0307692289352417 ,Loss_G: 6.445599555969238 ,D(x): 0.9967053532600403 ,D(G(z)) 3.621195822300496\n",
      "epoch: 99 ,i: 400 ,Loss_D: 0.03818528354167938 ,Loss_G: 6.675928592681885 ,D(x): 0.9978532195091248 ,D(G(z)) 11.007481029143866\n",
      "epoch: 99 ,i: 450 ,Loss_D: 0.11289560049772263 ,Loss_G: 3.6772146224975586 ,D(x): 0.9088780879974365 ,D(G(z)) 0.028540389014212797\n",
      "epoch: 99 ,i: 500 ,Loss_D: 0.042438533157110214 ,Loss_G: 6.068838119506836 ,D(x): 0.9733372926712036 ,D(G(z)) 1.4986457080152353\n",
      "epoch: 99 ,i: 550 ,Loss_D: 0.04857166111469269 ,Loss_G: 7.060900688171387 ,D(x): 0.9997895956039429 ,D(G(z)) 25.481425988126908\n",
      "epoch: 99 ,i: 600 ,Loss_D: 0.16490396857261658 ,Loss_G: 6.187887668609619 ,D(x): 0.9839504957199097 ,D(G(z)) 20.197323651273216\n",
      "epoch: 99 ,i: 650 ,Loss_D: 0.03257507458329201 ,Loss_G: 6.096195220947266 ,D(x): 0.9941173791885376 ,D(G(z)) 3.649319633601441\n",
      "epoch: 99 ,i: 700 ,Loss_D: 0.019177762791514397 ,Loss_G: 7.497900009155273 ,D(x): 0.9895639419555664 ,D(G(z)) 3.3926380636432407\n",
      "epoch: 99 ,i: 750 ,Loss_D: 0.01133404579013586 ,Loss_G: 6.794633865356445 ,D(x): 0.9987457990646362 ,D(G(z)) 2.1957521334085754\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for epoch in range(epochs):\n",
    "    for i, x_data in enumerate(data_load,0):\n",
    "        #先训练判别器D\n",
    "        net_D.zero_grad()\n",
    "        real_data=x_data[0].to(dev)\n",
    "        b_size=real_data.shape[0]\n",
    "        label=torch.full((b_size,),real_label,device=dev)\n",
    "        out_pred=net_D(real_data).view(-1)\n",
    "        cost_real=loss(out_pred,label)\n",
    "        cost_real.backward()\n",
    "        D_x=out_pred.mean().item()\n",
    "        noise=torch.randn(b_size,in_size,1,1,device=dev)\n",
    "        fake=net_G(noise)\n",
    "        label.fill_(fake_label)\n",
    "        out_pred=net_D(fake.detach()).view(-1)\n",
    "        cost_fake=loss(out_pred,label)\n",
    "        cost_fake.backward()\n",
    "        D_G=out_pred.mean().item()\n",
    "        #累加误差\n",
    "        loss_D=cost_real+cost_fake\n",
    "        #更新D\n",
    "        optimizer_D.step()\n",
    "        #更新G\n",
    "        net_G.zero_grad()\n",
    "        label.fill_(real_label)\n",
    "        out_pred=net_D(fake).view(-1)\n",
    "        loss_G=loss(out_pred,label)\n",
    "        loss_G.backward()\n",
    "        D_G_2=out_pred.mean().item()\n",
    "        optimizer_G.step()\n",
    "        if i%50==0:\n",
    "            print('epoch:',epoch,',i:',i,',Loss_D:',loss_D.item(),',Loss_G:',loss_G.item(),',D(x):',D_x,',D(G(z))',D_G/D_G_2)\n",
    "        loss_G+=loss_G.item()\n",
    "        loss_D+=loss_D.item()\n",
    "    if (iters%20==0) or ((epochs==epoch-1) and (i==len(data_load)-1)):\n",
    "        with torch.no_grad():\n",
    "            fake=net_G(fixed_noise).detach().cpu()\n",
    "        img_list.append(vutils.make_grid(fake,padding=2,normalize=True))\n",
    "        i=vutils.make_grid(fake,padding=2,normalize=True)\n",
    "        fig=plt.imshow(np.transpose(i,(1,2,0)))\n",
    "        plt.axis('off')\n",
    "        plt.savefig('./data/%d_%d.png'%(epoch,iters))\n",
    "    iters+=1\n",
    "torch.save(net_G.state_dict(),'./data/net_G.pt')\n",
    "torch.save(net_D.state_dict(),'./data/net_D.pt')"
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